NVIDIA

NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Development Engineer; you will collaborate with multi-functional groups. SWQA Developer Engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA Engineer can improve productivity or optimize test plan. As a SWQA Developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What you’ll be doing: - Review product requirements and develop test matrix. - Build test plan, design test case, execute and report test progress, bugs, and results to management. - Automate test cases and assist in the architecture, crafting and implementing of test frameworks. - Manage bug lifecycle and co-work with inter-groups to drive for solutions. - In-house repro and verify customer issues/fixes. What we need to see: - BS or higher degree or equivalent experience in CS/EE/CE plus equivalent with 2+ years QA experience. - Proficient in Unix/Linux and shell/python programming skills. - Rich experience in test cases development, tests automation in API/UI and failure analysis. - Solid experience with AI development tools, including creating test cases, automating test cases, and ensuring comprehensive code coverage, among other related tasks - Good knowledge and hands-on experience in model testing and LLM benchmarking - Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc. - Excellent communicator, fluent written and verbal English. - Good teamwork with ability to work independently. - Passion to learn new hardcore technology. Ways to stand out from the crowd: - Experience working with NVIDIA GPU hardware is a strong plus - Background in deep learning frameworks is a plus - Experience in parallel programming ideally CUDA/OpenCL is a plus

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We are looking to grow our company and establish teams with the most thoughtful people in the world. We’re looking for a highly motivated, creative Factory System Software and Diagnostics Integration engineer to join the Datacenter Platform Software team. You will play a crucial role in coordinating factory projects, guiding cross-functional teams, and collaborating with stakeholders to ensure the successful delivery of firmware, software and diagnostics that align with business objectives, as well as analyzing, evaluating, and improving factory processes. This role is for NVIDIA's GPU or DPU based products. Join us at the forefront of technological advancement. What you’ll be doing: - You will Lead Factory Validation projects from Software, Firmware and Diagnostics perspectives, ensuring successful implementation, integration, and standardization across multiple locations. - Lead the integration and handover of the Software, Firmware and Diags for all products. - Act as a primary consultant, offering strategic direction and leadership to the engineering teams. - Engage with ODMs and cross-functional teams to collect and analyze factory requirements, delivering solutions that meet both business and operational needs. - Analyze Factory processes, systems, and workflows to identify areas for improvement and optimization. - Develop and maintain detailed documentation, including system requirements, processes and standard operating procedures (SOPs). Collaborate across teams to design, configure, and implement changes to factory ensuring seamless integration and minimal disruption. - Perform system testing, validation, and fixing to ensure exact functionality and alignment with factory requirements. - Monitor, collect, and analyze data to identify and address issues, and propose solutions to enhance system reliability and efficiency. Collaborate with vendors and external partners to evaluate, select, and implement new factory systems or software/firmware upgrades. What we need to see: - 5+ years of relevant experience. - BS, MS, or PhD in EE/CS or related field of education (or equivalent experience). - 2-5 years of having worked as an Integration Engineer at Factory settings. - Strong knowledge of server manageability, bring up and deployment in data centers. Proven understanding of Firmware, Diagnostics for x86 and ARM servers - Experience working with ODM/OEMs to deliver quality servers. - Strong and demonstrable skill in python, C/C++, and shell scripting. - Experience programming and debugging skills for GPU platforms. - You should possess excellent written and oral communication skills, excellent work ethics, a deep sense of teamwork, love to produce quality work and commitment to finish your tasks every single day. You are a self-starter who loves to find creative solutions to complicated problems and hands on with coding. Ways to stand out from the crowd: - Worked on Factory integration or hardware bring up projects. - Hands on with x86 or ARM system architecture. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.”   We're   looking to grow our company and establish teams with the most thoughtful people in the world. We are the Datacenter System Software team, and we are looking for a highly motivated, creative Engineering Manager to drive Factory System Software and Diagnostics Integration end to end. You will build and lead a global engineering team delivering embedded code, application programs, and diagnostic updates. These updates support factories building NVIDIA's GPU- and DPU-based products. This includes tightly coupled rack-scale systems such as GB200/GB300 NVL72 and next-generation platforms. The work covers concurrent NPI ramps and sustaining production. You will partner with system architects, firmware developers, SWQA, product engineering, compliance and security teams, program and product management, and ODM/CM manufacturing partners to ensure the highest-quality releases land on factory floors — and that no bug is discovered there first.   Join us at the forefront of technological advancement. What you’ll be doing: - Build, lead, mentor, and grow a global factory engineering team spanning the US and Taiwan — operating a follow-the-sun coverage model with on-site presence at ODM/CM partner factories. Own hiring, career development, calibration, and succession planning. - Define Factory readiness scope and workflows for rack scale products coordinating multi-functionally with product management, technical   architects   and program management. Deliver those workflows through the validation matrix, ensuring delivered firmware and software is of the highest quality. Solutions must scale and be resilient. - Own technical leadership for how firmware, software, and diagnostics releases reach factories building rack-scale systems. These systems include tightly coupled   compute   and switch trays. Build the end-to-end infrastructure and workflows that ensure every release arrives with efficient quality. - Left-shift release quality: partner with all matrixed organizations — developers, SWQA, and product engineering — in a fast-moving environment with end-to-end CI/CD so that no bug is first found at a factory site. Enforce well-placed quality gates at every product landmark, publish and track indicators at a regular cadence, and report release progress to collaborators and executives. - Own the factory escalation path: triage SLAs, 24×7 coverage, failure root-cause   and deflection, and   bonepile   burn-down — minimizing line-down time through NPI ramps and mass production. - Shape the team's roadmap and drive innovation with a strong focus on automation and AI-assisted validation and triage — automating station readiness, firmware-update flows, and log triage so senior engineering time shifts from setup to analysis. - Continuously analyze factory processes, systems, and workflows to   identify   improvement and optimization opportunities; remove bottlenecks, document and publish standard operating procedures (SOPs), and ensure the team performs in the most efficient and transparent way against measurable targets. What we need to see: - 10+ overall years in the software industry with specialization in system software and/or firmware development. - 3+ years of engineering management or technical leadership experience, including building and leading geographically distributed teams. - BS, MS, or PhD in CS, CE, EE, or a related technical field — or equivalent experience. - Proven   track record   of shipping scalable server products through factory ramps — from NPI bring-up to mass production — collaborating with hardware, firmware, manufacturing, diagnostics, and QA teams. - Experience working with ODM/OEM partners to deliver quality servers and solutions for large-scale data centers. - A self-starter who loves finding creative solutions to complicated problems, with excellent written and oral communication skills — including executive-level reporting — strong work ethic, and dedication to teamwork. - Flexibility to work and communicate effectively across teams, partners, and time zones. Ways to stand out from the crowd: - Experience leading bring-up for sophisticated rack-scale   compute   architectures like GB200/GB300 NVL72. - Familiarity with manufacturing test flows (L6/L10/L11/L12 stations), factory test coverage, and MES integration. - Hands-on experience with x86/ARM system architecture and coding (C/C++, Python).     Experience with SCM (Git, Perforce) and project management tools (Jira). - Track record   of integrating AI/LLM tooling into engineering workflows — for triage, validation, log analysis, or test generation. - Experience standing up follow-the-sun support organizations with measurable response SLAs. NVIDIA is widely considered to be one of   the technology   world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If   you're   creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. We are now looking for a Senior Mixed Signal Design Engineer to be part of the Mixed Signal design team building next generation NVLINK. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. The team is responsible for the development and implementation of high-speed interfaces and analog circuits. Gain hands-on experience taking innovative integrated circuit designs at data rates of 100Gbps and higher from concept through silicon characterization. Come join our dynamic team today! What you'll be doing: - You will be part of the design and implementation of high-speed interface circuits; Have the chance to create projects including high speed transceivers and high frequency PLLs. - Become involved in the design, simulation, and verification of mixed-signal circuits; Lead mask designers, provide mentorship for floorplan and layout design. - Provide support to the lab characterization of silicon and pursue the challenges of circuit design in deep submicron CMOS. - You will take designs through implementation and productizing. - Collaborate with multi-functional teams. What we need to see: - BS or MS in Electrical Engineering, PhD preferred (or equivalent experience) - 8+ years of design experience in CMOS analog / mixed-signal circuit - Working knowledge of Cadence custom design tools, circuit simulator, timing analysis tool; Your extensive design experience in Data Converters, Tx, Rx, CDR, PLL for high-speed IO interfaces. - Someone who's an exceptional teammate with good interpersonal skills; Validated experience in leading and mentoring designers. - In-depth understanding of deep submicron CMOS process and related circuit design issues; Proven experience in silicon bring-up, debugging and use of lab instrumentation is required. - Knowledge in system level timing budget, signal integrity, and power integrity is a plus; Experience in Verilog, Matlab, Nanotime is helpful. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, we want to hear from you.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence. The NVIDIA System-On-Chip (SOC) group is looking for an experienced ASIC Verification Engineer! In this position you will have the chance to create a high-level and broad impact at NVIDIA working on a system-level IP responsible for measuring performance on multiple projects. Your focus will be on verifying and improving the related verification methodologies for the corresponding design (RTL). For this position, you should have real passion for verification methodologies and implementation that enable high quality system-level IP design and robust verification at multiple environment levels (e.g., unit, sub-system, and SOC). What you'll be doing: - Design and maintain the unit level/sub-system Verification environment. - Understand the architecture specifications, develop and carry out the test plan to verify the design. - Create UVM components, sequences, tests and scoreboards. - Sign off on the verification efforts with very high-quality code and functional coverage. - Launch regressions, resolve the issues, and make forward progress towards achieving the DV milestone targets - Automate the manual steps involved in launching build, regression, and triage. - Collaborate with architects, designers, and software engineers to achieve project goals. - Proactively contributes to improving the efficiency of the testbenches by embracing the latest techniques. - Responsible for end-to-end verification of IPs, ensuring the highest quality delivery. What we need to see: - Bachelor’s or Master’s degree in Computer or Electrical Engineering (or equivalent experience) with 3 years of relevant experience. - Proficient with System Verilog, UVM required and OOPS based programming. - Strong coding skills in Python or other industry-standard scripting languages. - Strong understanding of RTL design (Verilog). - Good understanding of computer architecture fundamentals. - Familiarity with verification tools such as VCS or equivalent simulation tools, and debug tools like Verdi. With industry-leading salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. The most forward-thinking engineers in the world do their life’s work at NVIDIA. If you're creative and autonomous, with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's Deep Learning GPUs have ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are growing our company and the team with the smartest people in the world. We are looking for extraordinary Software Engineers to develop and productize NVIDIA's DRIVE software. As a member of NVIDIA's Solution Engineering team, you will adapt DRIVE solutions to various car platforms equipped with different sensors. We are looking for a Senior Safety Architect with a good   grasp of Hardware and Software Architectures,   expertise   in Automotive SPICE & ISO26262 and applying   ISO26262 to safety-critical automotive components and systems. What you will be doing: - Lead the safety architecture discussions for SW components and directly   interface with   customers to support DRIVE software safety solutions. - Epitomize the DRIVE Software Functional Safety and SOTIF strategy to customers. - Collaborate with customers to draft the DIA for programs per ISO26262. - Engage with   customers to understand and   identify   the safety requirements on DRIVE software. - Continuously evolve and support requirements gathering process and traceability flow. - Actively coordinate with cross-functional engineering teams to meet customers’ safety requirements and to drive complex issues to closure. - Work with customers’ safety teams to integrate NVIDIA’s   SEooC   software components to build overall safety   case   for their products. - Participate in architectural explorations which include feasibility studies, safety   evaluations   and data analysis. - Influence NVIDIA’s DRIVE Safety Architecture & Framework evolution with inputs and recommendations into the design and architecture choices. What we need to see: - BS/MS or equivalent experience. - 10+ years of overall experience   and with   3+ years of automotive industry experience. - Sound knowledge of functional safety architecture to meet   ISO26262   standard. - Hands-on experience implementing parts 3 and 4 of ISO26262. - Strong background in embedded software development and deep knowledge of product development lifecycle. - Proficiency   with safety architectural analysis of ADAS or L2/ L3 autonomous driving stack is   preferred.. - Experience with   developing fault handling strategies and degraded modes of operation. - Effective written and verbal communication regardless of audience or issue complexity. - Proven   track record   with shipping safety systems. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression , sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can take on, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. We are looking for an ASIC Clocks Design Engineer to join the team. Our team crafts all aspects of GPU and CPU clocking. The team collaborates with the front design team to understand the clocking requirements for the chip. The clocks team interacts with the floor-planning and back end team to help craft the physical floorplan of the chip. The team explains the programming model to the SW team to come up with an efficient clock programming sequence. The team works with the silicon solution team to triage silicon or programming bugs in the lab. What you'll be doing: - As a Clocks team member, you will be architecting the clock domain to satisfy functional, physical and testing design requirements. - Engage with multiple teams and design the GPU or CPU clocks to satisfy all the architectural/design/physical constraints. - Improve Power, Performance, and Area (PPA) of innovative NVIDIA chips by evaluating trade-offs across DFx, Physical Implementation, Power Optimization and Ease of timing closure to innovate and implement new Clocking topologies in RTL. - Collaborate with Physical design and timing team to evaluate Clocking concerns and develop solutions for supporting high speed Clocking. - Together with other team members, we deliver clock RTL information to GPU, CPU and SOC verification team, timing and DFT teams. - Get involved in end-to-end cycle of ASIC execution starting from micro-arch, design implementation, design fixes, sign-off checks and all the way to Silicon bringup. What we need to see: - Bachelor's degree or higher in Electrical Engineering (or equivalent experience). - Understanding of logic optimization techniques and PPA trade-offs. - Shown ability to collaborate with multiple teams. - Experience in RTL design (Verilog), verification and logic synthesis. - Strong coding skills in Python or other industry-standard scripting languages. Ways to stand out from the crowd: - Understanding of sub-micron silicon issues like noise, cross-talk, and OCV effects is a plus. - Implementing on-chip clocking networks is a bonus. NVIDIA is widely considered to be the leader of AI computing, and one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until June 7, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is looking for Senior Networking (ETH/IB) Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What you'll be doing: - Primary responsibilities will include building AI/HPC infrastructure for new and existing customers. - Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting. - Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement. - Maintain services once they are live by measuring and monitoring availability, latency, and overall system health. - Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements. What we need to see: - BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields. - At least 5+ years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture - Proficiency in configuring, testing, validating, and resolving issues in LAN and InfiniBand networks, especially in medium to large-scale HPC/AI environments. - Advanced knowledge of EVPN, BGP, OSPF, VXLAN protocols. - Hands-on experience with network switch/router platforms like Cumulus Linux, SONiC, IOS, JunosOS, and EOS. - Extensive experience delivering automated network provisioning solutions using tools like Ansible, Salt, and Python. - Ability to develop CI/CD pipelines for network operations. - Strong focus on customer needs and satisfaction. - Self-motivated with leadership skills to work collaboratively with customers and internal teams. - Strong written, verbal, and listening skills in English are essential. Ways to stand out from the crowd: - Familiarity with cloud networks (AWS, GCP, Azure) is a plus. - Linux or Networking Certifications. - Experience with High-performance computing architectures. Understanding of how job schedulers(Slurm, PBS) work. - luster management technologies knowledge (bonus credit for BCM (Base Command Manager).) - Experience with GPU (Graphics Processing Unit) focused hardware/software.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-X Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions in AI for Chip Design and AI for Predictions in various use cases in manufacturing testing on some of the industry's most complex semiconductor chips. What you'll be doing: - As a senior member in our team, you will work on innovating in the DFT Power, Thermal & Voltage Noise Methodology areas. - This will include working on groundbreaking low power & thermal solutions for our manufacturing tests to be enabled at conditions that push the boundaries for our datacenter GPUs. - You will work with multi-functional teams including Product Development & Power Architecture, implementing brand-new methodologies on hard-to-solve problems for improving our outgoing quality of chips. - You will work on post-silicon data analysis for power to architect the next-gen solutions. - In addition, you will help develop and deploy DFT methodologies for our next generation products  using Applied ML & Gen AI solutions. - You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: - BSEE (or equivalent experience) with 12+, MSEE with 10+, or PhD with 6+ years of experience in DFT design & power - Understanding of fundamental DFT topics and VLSI areas of power, timing & voltage noise - Experience in Power Analysis, Thermal Analysis & IR Drop tools is a plus. - Experience in application of AI for EDA-related problem-solving is a plus. - Excellent knowledge in using statistical tools for data analysis & insights. - Good exposure to multi-functional areas including RTL & clocks design, STA, place-n-route and power. - Experience in Silicon debug and bring-up on the ATE or SLT platforms. - Be able to think like a programmer so that this can be translated into action using AI Coding harnesses - Outstanding written and oral communication skills with the curiosity to work on rare challenges. Ways to stand out from the crowd: - Experience in managing DFT Power Methodology for designs - Experience in post-silicon debug for thermal & IR Drop - Good understanding of technology and passionate about what you do - Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic environment NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 196,000 USD - 310,500 USD for Level 5, and 232,000 USD - 368,000 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking an Applied AI Engineer to lead end-to-end solution development — spanning data generation, model training, orchestration, and agentic automation — for timing and constraint analysis workflows. You will be part of a cross-disciplinary team building intelligent systems that learn from sign-off data, reason across flows, and assist engineers in achieving faster and more predictable closure. What You’ll be Doing: - Architect and develop AI-driven solutions for static timing, constraints quality, and closure prediction. - Integrate heterogeneous data sources — timing reports, constraint graphs, design metadata, silicon correlation — into structured knowledge bases and training pipelines. - Develop autonomous analysis agents that interact with timing tools (e.g., PrimeTime, Nanotime, Tempus) to perform multi-corner, multi-mode optimization and constraint debugging. - Implement scalable orchestration across Flow-Server and Digital Engineer platforms, enabling AI-in-loop decision-making for sign-off readiness. - Collaborate with methodology and sign-off teams to validate models on live projects, improving coverage, predictability, and engineering productivity. - Build interpretable AI pipelines using graph neural networks, large language models, and process-aware reasoning engines for timing closure recommendations. - Be responsible for the end-to-end lifecycle — from data curation and model training to deployment, monitoring, and continuous improvement in production environments. What We Need to See: - BS (or equivalent experience) in Electrical or Computer Engineering with 12+ years of experience in AI/ML solution development, ideally for EDA, semiconductor, or complex data domains - Strong background in VLSI/ASIC design — with deep understanding of timing, constraints, STA, or sign-off workflows. - Proficiency in Python, PyTorch/TensorFlow, and graph or agentic AI frameworks (e.g., LangGraph, LangChain, Ray, NetworkX). - Experience developing data pipelines, knowledge graphs, or process models for structured engineering data. - Working knowledge of timing tools (PrimeTime, Nanotime, Tempus) and scripting integration with EDA environments. - Experience with AI orchestration frameworks, reasoning based on prompts, and multi-agent automation is highly desirable. - Strong problem-solving skills, technical depth, and a mentality for experimentation and continuous learning. Ways to stand out from the crowd: - Experience with constraint validation, false-path detection, and timing-exception modeling. - Prior exposure to AI in physical design automation, Silicon/process modeling, or EDA flow automation. - Contributions to open-source AI or flow automation projects. - Publications or patents in AI for design automation or semiconductor engineering Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 196,000 USD - 310,500 USD for Level 5, and 232,000 USD - 368,000 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are seeking a highly technical and strategic Senior Developer Relations Manager to join NVIDIA Digital Health, with a focus on engaging researchers and AI developers across industry and academia who are building AI for digital health. In this pivotal role, you will work directly with healthcare AI developers to champion the adoption of NVIDIA’s AI and accelerated computing platforms. The ideal candidate brings a blend of deep research expertise combined with a passion for developer advocacy and a talent for communicating how NVIDIA technology can solve complex, research and real-world deployment challenges. A core initial mission will be to help drive a collaborative digital health consortium focused on industry-relevant benchmarks and synthetic evaluation recipes for digital health AI models and agents. What You'll Be Doing: - Develop and maintain deep technical expertise in digital health AI. Serve as the trusted technical advisor, problem solver, and champion for researchers and developers across the digital health ecosystem. Work with cross-functional partners to drive adoption of NVIDIA technologies. - Accelerate digital health AI research workloads by demonstrating and integrating the NVIDIA software stack, including tools, libraries, SDKs, NIMs, and blueprints, into research platforms, applications, and pipelines. - Guide partners and research collaborators through onboarding and integration by providing technical resources such as sample code, evaluation harnesses, training recipes to accelerate research and foster co-innovation. - Map and monitor the researcher ecosystem to identify growth opportunities, including healthcare AI agents, foundation models, model evaluation, synthetic data generation, post-training, inference, and deployment tooling. - Engage research leaders across academia and industry to drive best-practice integrations, resolve technical challenges, surface new workflows, and channel critical field insights back to NVIDIA product teams. - Help create open benchmark datasets, reproducible synthetic data generation pipelines, model evaluation harnesses, fine-tuning recipes, technical papers, and blogs. - Represent NVIDIA at research conferences, industry forums, hackathons, technical meetups, and partner events while supporting early access programs, product launches, go-to-market activities, and lighthouse collaborations. What We Need to See: - MS or Ph.D degree or equivalent experience in Computer Science, Machine Learning, Clinical Informatics, Computational Medicine, Data Science, Electrical Engineering, Applied Math, or a related technical field. - A minimum of 12+ years of overall professional experience in AI/ML, applied research, software engineering, developer relations, technical partnerships, product management, or solution architecture, including 5+ years of direct hands-on experience in healthcare AI, digital health, or life sciences AI. - Proven track record in leading developer programs across healthcare research organizations. - Significant technical depth in AI tools and model architectures including LLMs, VLMs, speech models, agentic workflows, pre+post-training, and inference optimization. - Experience leading research collaborations with engineering, product, and research teams, including architectural design, model evaluation, benchmark design, code reviews, technical mentorship, and delivery of technical talks or workshops. - Ability to structure and implement technical engagements, negotiate requirements, prioritize issues, and collaborate with internal or external collaborators across product, engineering, research, sales, legal, privacy, and marketing teams. - Skilled at distilling deeply technical concepts for audiences from researchers and engineers to product leaders and executives, with high empathy for developers and researchers and comfort working in a fast-paced, highly matrixed environment. Ways to Stand Out from the Crowd: - Hands-on experience building or optimizing AI solutions, such as clinical foundation models, healthcare speech systems, or digital health agents in production or research settings. - Familiarity with accelerated computing and AI platforms relevant to healthcare AI, such as NeMo, Nemotron, MONAI, Parabricks and BioNeMo. - Successful history of building and scaling developer communities and research collaborations in healthcare AI. - Expertise in building frameworks to capture developer and researcher sentiment, market shifts, and ecosystem dynamics, translating real-time signals into healthcare AI strategy and product roadmap input. - Published research, patents, standards work, public datasets, open benchmarks, or open-source contributions in healthcare AI. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 6, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking an Engineering Manager to lead the development of an agentic platform for observing, debugging, and optimizing GenAI models deployed at scale. In this role, you will lead a team building an agentic platform that provides visibility into model behavior, inference performance, reliability, and cost across large-scale GenAI workloads. This agentic platform will capture, correlate, and analyze logs, traces, metrics, and performance signals across large scale LLM and VLM deployments. It will help engineers understand model-serving behavior, find regressions, optimize latency and throughput, and improve the reliability of GenAI systems in production. You will work across the NVIDIA AI software stack with teams focused on inference serving, model optimization, distributed systems, GPU performance, and production operations. This is a highly cross-functional role for someone who understands deep learning systems, observability, and large-scale software platforms, and who is excited about building agentic workflows that help teams reason over complex telemetry and performance data. What You’ll Be Doing: - Lead, mentor, and grow a team building an agentic platform for monitoring and improving large-scale LLMs and VLMs in production. - Build systems that collect, correlate, and analyze telemetry across inference servers, GPUs, schedulers, model runtimes, and customer-facing APIs. - Develop agentic workflows that help engineers identify root causes, explain regressions, and recommend performance optimizations. - Collaborate with internal customers and business units to align priorities and deliver production grade platform capabilities. What We Need To See: - BSc, MS, or PhD in Computer Science, Computer Engineering, or equivalent experience. - 8+ years of relevant software engineering experience, including 3+ years in engineering management or technical leadership. - Experience leading software engineering teams building large-scale distributed systems, observability platforms, ML infrastructure, or production AI systems. - Strong understanding of LLM/VLM inference systems, deployment patterns, and production performance challenges. - Experience with logs, metrics, traces, profiling, alerting, dashboards, or incident/debugging workflows. - Strong programming, debugging, performance analysis, and test design skills. - Ability to work across organizations and align technical priorities with product and business goals. - Excellent communication and collaboration skills. Ways To Stand Out From The Crowd: - Background in GPU performance analysis, distributed inference, model serving optimization, or reliability engineering. - Experience building observability or telemetry platforms for AI, ML, cloud, or distributed infrastructure. - Experience with OpenTelemetry, Prometheus, Grafana, Jaeger, ClickHouse, Elastic, or similar observability tools. - Experience building agentic systems that reason over logs, traces, performance data, incidents, or operational workflows. - Hands-on experience with production GenAI serving systems and metrics such as TTFT, TPOT, throughput, queueing delay, GPU utilization, KV cache pressure, error rates, and cost per token. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's deep learning platform has already made a major impact to the field and is broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need hardworking and creative people to help us dive into these exceptional opportunities in GPU application in the enterprise solution space. We are now looking for an expert Senior Hardware Applications Engineer with the ability to focus on customer enablement of datacenter products, work with customers and internal teams to resolve hardware, firmware and software issues, and provide key technical collateral. This is a highly technical engineering role that is responsible for providing best-in-class support to NVIDIA's enterprise customers. We are looking for someone who has superb interpersonal skills and who can understand, explain, and solve customer problems. This position will focus on NVIDIA enterprise datacenter products in workstation and server applications. What you'll be doing: - Perform system design reviews for data center applications to ensure partner designs meet NVIDIA guidelines. - Work on resolving system integration issues related to thermal, mechanical, electrical, PCIe and GPU interconnect interfaces including out-of-band management services. - Understand system design requirements for High Performance Computing and AI workloads to drive platform configuration guides for x86 and ARM servers. - Conduct the installation, configuration and bring-up of enterprise server hardware. - Work directly with our NVIDIA customers, and analyze data to answer questions, reproduce errors, resolve same, or escalate customer issues. - Be involved in customer interaction, customer communication via conference calls or face to face meetings - Familiarize yourself with performing hardware debug using oscilloscopes and analyzers to qualify, validate and solve NVIDIA products for customer systems. - Track and file new bugs, and reproduce issues as needed. - Create product specifications, hardware design guides, application notes, and other supporting technical collateral. What we need to see: - BS, MS, or PhD in Electrical Engineering, Computer Engineering or Systems Engineering, related field or equivalent experience. - 3+ years of proven experience in supporting enterprise data center products for x86 or ARM architecture. - Have strong analytical skills and past experience in reviewing enterprise system design and CPU architecture. - Understanding of x86 and ARM system architecture for server design including BMC, security and out-of-band management. - Professional-level interpersonal skills, including your ability to adjust your communication to the technical level of the audience. - An innate capability to accurately and succinctly communicate procedures, results, and recommendations to customers. - Experience with using lab tools such as oscilloscopes, multi-meters and logic analyzers and possess a nurtured knowledge of Linux, and be very comfortable working in various Linux environments as well as with Windows OS. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts focused on inference for Generative AI and Large Language Models (LLMs). You will also collaborate with a diverse set of internal teams on performance analysis and modeling of inference software. You should be comfortable working in a dynamic environment, and have experience with Generative AI, LLMs and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! What You Will Be Doing: - Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions - Dynamically engaging with developers, scientific researchers, and data scientists, gaining experience across a range of technical areas - Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform - Working closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions - Analyzing performance and power efficiency of AI inference workloads on Kubernetes - Some travel to conferences and customers may be required (20%) What We Need To See: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow - Strong fundamentals in programming, optimizations, and software design, especially in Python - Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments - Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments - Excellent knowledge of the theory and practice of LLM and DL inference - Excellent presentation, communication and collaboration skills Ways To Stand Out From The Crowd: - Prior experience with DL training at scale, deploying or optimizing DL inference in production - Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM , Dynamo , TensorRT , TensorRT-LLM - Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design - Familiarity with parallel programming and distributed computing platforms NALASAHiring Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking a Sr Network Security Engineer to implement and maintain robust security across on-premise and cloud environments - enabling business verticals that span Graphics Drivers to AI and Deep Learning. In this role, you will lead the deployment and management of critical security infrastructure, including next-generation firewalls, load balancers, and advanced threat detection systems, safeguarding our hybrid cloud and on-premise networks while driving compliance across the organization. The ideal candidate brings deep expertise in multi-cloud architectures and cybersecurity, a proven track record of supporting large-scale, high-availability networks, and hands-on experience operating with hyperscaling environments. You’re a decisive problem-solver who thrives in fast-paced settings and moves with urgency to meet the demands of modern infrastructure. What You Will Be Doing: - Design & Integrate: Collaborate with the network architecture team to review and comment on network designs. - Manage & Optimize Infrastructure: Lead the deployment, management, and troubleshooting of firewall, load balancing, and IDS/IPS solutions across both on-premise and cloud environments. - Enhance Visibility & Intelligence: Evolve our security feature set by using telemetry and advanced analytics to improve network observability and proactive threat detection. - Governance & Compliance: Define and maintain comprehensive security guidelines for on-premise and cloud deployments, ensuring consistent alignment with compliance and defense-in-depth standards. - Threat Mitigation: Orchestrate rigorous vulnerability management, including patching and bug scrubs, to proactively eliminate potential threat vectors. - IAM Strategy: Design Identity and Access Management (IAM) policies and controls specifically for services owned and operated by the global networking team. - Operational Excellence: Serve as a key stakeholder in security reviews and ACL approvals, ensuring safe, efficient, and resilient network operations. - Incident Response & Triage: Lead incident response efforts by investigating security alerts, conducting root cause analysis, and executing remediation plans in alignment with security incident handling frameworks. - Operational Enablement: Partner with the global operations team to ensure they have the necessary operational tools, documentation, and actionable information required to provide rapid first-response to network and security incidents. What We Need To See: - Network & Cloud Security Architecture: Proven expertise in secure cloud-native and hybrid network architectures across major CSPs (AWS, GCP, Azure, OCI), ensuring seamless connectivity and stringent security posture. - Secure Network Infrastructure: Proficiency in securely deploying and managing Fortigate (FortiManager), Arista, Cisco, and Cumulus OS devices. - Advanced Threat Protection: Comprehensive operational knowledge of IDS/IPS, SSL inspection, URL filtering, and anti-malware/bot mitigations to maintain high-throughput secured traffic. - Virtualization & Connectivity: Strong understanding of network virtualization (VRFs, VxLAN) and CSP-specific virtualized firewall deployments. - Dynamic Routing Protocols: Proficient in dynamic routing protocols such as BGP, OSPF, IS-IS to ensure resilient and efficient network connectivity. - Monitoring & Observability: Experience managing logging pipelines and telemetry tools such as Splunk and Grafana for proactive security oversight. - Professional Experience: 8+ years of dedicated network security experience with a Bachelor’s degree or equivalent experience, coupled with the ability to collaborate cross-functionally with global security teams. Ways To Stand Out From The Crowd: - Multi-Cloud Security Expertise: Deep proficiency in OCI, GCP, AWS, and Azure cybersecurity frameworks. - Infrastructure Proficiency: Working knowledge of Mellanox/Cumulus OS and network routing paradigms. - Automation & AI-Assisted Development: Proven ability to leverage Python, Shell scripting, and AI coding tools (e.g., Cursor, Claude Code) to build efficient automation, frameworks, and operational dashboards. - Large-Scale Experience: Demonstrated success in designing and securing hyper-scale network environments. - Innovation Outlook: Passion for driving progress through the adoption of groundbreaking technologies. NVIDIA is leading the way in ground breaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 208,000 USD - 333,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

In the NVIDIA Isaac team, we build tools that bring the power of the GPU to bear on one of today’s grand challenges: physical AI. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where we all work together to advance the frontiers of accelerated computing. We’re looking for a software engineer to join our team to develop simulation tools built for scientists and companies that are using machine learning to solve the future of robotics. You'll join a team of robotics engineers who work at the intersection of simulation and machine learning. Our goal is to build the industry's leading tool for evaluating robot foundation models in simulation. This mission builds on NVIDIA's history of creating virtual worlds using its groundbreaking technology on photorealistic rendering and physics simulation technologies. What you'll be doing: - Building simulation frameworks for training and evaluating robot foundation models on top of NVIDIA's Omniverse platform. - Working as part of a high-paced software engineering team: design/code reviews, testing, continuous integration, deployment. - Training and evaluating robot foundation models. - Integrating modern LLM and agentic workflows into simulation and robotics workflows. - Working with researchers to translate ideas from research into products that can scale to NVIDIA's user base. - Keeping up to date with the state-of-the-art in robotics research. What we need to see: - MSc, PhD degree or equivalent in Computer Science, Robotics, or a related field. - 3+ years of experience in robotics and/or simulation. - Experience in software design and working on a significant software project. - Proficiency using Python and development experience with deep learning software stacks (Pytorch, Jax, etc.). Ways to stand out from the crowd: - Publications and/or projects that demonstrate excellence in moving the needle in the field of robotics. - Robot learning expertise with reinforcement learning and/or imitation learning, - Physics simulation expertise. - Experience with tools used in the NVIDIA robotics ecosystem (CUDA, warp, Isaac Lab, ROS). - Developing and maintaining open-source projects.

We are seeking a Senior NPI Program Manager (Operations). NVIDIA is growing in several areas, and we need our team to be instrumental in facilitating further growth and expansion. We need someone passionate about working on products that enable deep learning, artificial intelligence, advanced driver assistance systems (ADAS), high-performance computing, enterprise graphics and gaming to join the Silicon Operations Group. In this role, as an individual contributor, you will be responsible for the Operations NPI schedule and related milestones of taking a product from tape-out to production release. We require someone who has a strong engineering background with a keen interest in program management and can work in a dynamic environment. You are someone who thrives working on groundbreaking technology and enjoy working with people to take on problems. A Program Manager supporting Operations NPI needs to be able to see both the high-level view and be proficient in tracking and following up on detail. We desire someone who is independent and can excel in their role as the person-in-charge for their product representing all aspects of silicon bring-up in Operations. We want you to help us improve processes and efficiency to foster growth for the team and the company. What you'll be doing: - Track and communicate key results, constraints, risks, dependencies and clearly identify critical paths while working with ASIC, product, test, system, software engineering and planning teams and other program managers towards a common goal. - Handle cross-functional communications independently while working within a matrixed GM team and publish progress/roadblocks to upper management. - Bring diverse teams together to tackle complex problems and work towards closure. - Understand and collaborate in developing the Plan of Record (POR), ensuring qualification plans, checklists and specifications are in place to support production release. - Develop engineering wafer and hardware risk plans and own internal and external sample supply. - Lead and attend cross-functional NPI meetings related to your product and highlight key Ops issues and ensure that the product is ready for production. - Drive process improvement initiatives for NPI across Operations and cross functional teams. We will look to you to bring new and creative ways to improve overall efficiency and speed at which products are brought to market. - Own metrics for NPI supply commits, production ramp and release turning points and manage bring-up budgets/OPEX for NPI. - Develop processes and metrics for functional teams in Ops planning, engineering, logistics and quality teams. What we need to see: - 7+ years of proven experience in an engineering or technical/engineering program management role. - Bachelor's in EE (or equivalent experience), Master's preferred. - PMP or other Project/Program Management Certification is a plus. - Excellent leadership, problem-solving, decision-making and cross-functional influencing skills. - Proficiency in Program Management and planning tools. Ability to analyze and solution supply chain processes. - Excellent knowledge of semiconductor manufacturing flow and processes. - Strong verbal and written communications skills. - Have the ability to work independently and navigate ambiguous situations. With competitive salaries and a generous benefits package, we are widely considered to be technology industry's best employers. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. Come build the future with us! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Join the NVIDIA Developer Tools team and empower engineers throughout the world developing groundbreaking products in Automotive, VR, Gaming, Deep Learning, and High Performance Computing. See your efforts in action as developers and 3rd party tool developers use your products to debug, profile and analyze the correctness of their systems/applications using the products and low-level API that you contributed to as a member of the Developer Tools team. Innovate as you develop the debug and performance analysis capability of future generations of NVIDIA GPUs. Be a part of the team that brings new GPU technologies to market with sophisticated simulation/emulation systems and be among the first to breathe life into new silicon. NVIDIA is looking for a senior software engineer to join our efforts to advance the state of our Compute Sanitizer product to the next level. The position will be part of a dynamic, world-wide team that develops and maintains several desktop and mobile Developer Tools products that are hosted and targeting OSes including Windows, Linux, Android and other embedded system real time OSes (RTOS). What you’ll be doing: You will apply knowledge of compute programming models and compute architecture to build tools that provide actionable feedback to compute developers. You should be comfortable working in existing driver code and application code as well as writing new shared libraries and targeted performance tests, and have an eagerness to learn about new compute and graphics drivers, GPU architectures and operating systems. - Develop the Compute Sanitizer (which is a suite of memory checker) tools for GPUs running on Linux, Windows, and embedded operating systems. - Work with tools, compiler, architecture and driver teams to design, implement and verify new features in the Compute Sanitizer stack. - Work closely with internal and external partners including other peer organizations within NVIDIA. - Effectively estimate and prioritize tasks in order to create a realistic delivery schedule. - Write fast, effective, maintainable, reliable and well-documented code. - Provide peer reviews to other engineers, including feedback on performance, scalability and correctness. - Document requirements and designs, and review documents with teams throughout NVIDIA. - Mentor junior engineers. What we need to see: - BS or MS in Computer Science or equivalent experience - 8+ years of experience - Strong programming ability in C, C++, Assembly Language and scripting languages - Excellent system programming expertise: memory management, processes/threads management, debugging and profiling - Excellent knowledge of computer architecture of x86 or ARM CPUs - Strong problem solving and debugging skills - Familiar with low-level programming using assembly languages - Source control understanding (git, Perforce, etc.) - Ability to self-manage, communicate, and adapt in a fast paced, high demand environment with changing priorities and direction - Excellent communication skills, written and verbal Ways to stand out from the crowd: - CUDA/OpenCL knowledge - Experience with code patching - ELF/DWARF knowledge Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is the pioneer of GPU-accelerated computing. We target the world’s most demanding users - gamers, designers, and scientists. We’ve reinvented modern computer graphics, PC gaming, and accelerated computing. Our work in AI, deep learning, and self-driving cars is transforming entire industries and reshaping the world! The NVIDIA IT Infrastructure Compliance team plays a critical role in ensuring our technology infrastructure, digital systems, and external partner integrations are secure, compliant, efficient, and resilient. As we continue to scale our global manufacturing footprint, securing our supply chain ecosystem is paramount. We are seeking a highly motivated, technically sharp Senior IT Infrastructure Compliance Engineer to lead and execute comprehensive risk assessments across our Global Manufacturing Operations and External Partner ecosystem (encompassing Tier-1 Foundries, ODMs, OSATs, and critical logistics providers). In this role, you will evaluate the IT general controls, cybersecurity posture, data integrity, and operational resilience of the interconnected systems linking NVIDIA to our manufacturing partners. Acting as a trusted technical advisor, you will identify systemic risks in supply chain automation, intellectual property (IP) protection, B2B data exchanges, and shop-floor control systems, ensuring our global partner network operates securely, compliantly, and at peak efficiency. What You Will Be Doing: - Audit Execution & Leadership: Plan, lead, and execute complex IT and security audits focusing on manufacturing systems (MES), Product Lifecycle Management (PLM), Enterprise Resource Planning (ERP - SAP), and supply chain B2B integrations. - Third-Party & Partner Risk Assessment: Evaluate the IT risk and security posture of external manufacturing partners (Foundries, OSATs, and Subcontractors). Assess their compliance with NVIDIA’s security standards, data protection protocols, and intellectual property safeguards. - Serve as the primary on-site IT contact for factory users and stakeholders within the North and South America regions, ensuring effective communication and coordination with remote and global IT teams across multiple domains (including networking, storage, and applications). Additionally, manage urgent Tier-3 escalations with third-party IT vendors regarding network connectivity, servers, client systems, and production tools. - Cybersecurity & Infrastructure Review: Audit network segmentations, access controls, APIs, and data transmission protocols that facilitate automated data exchange between NVIDIA and external manufacturing facilities. - Compliance & Frameworks: Evaluate IT environments against industry frameworks (ISO 27001 / SOX) to ensure data privacy, financial integrity, and regulatory compliance. - Data Integrity & Analytics: Assess the accuracy and completeness of yield data, inventory reporting, and supply chain metrics flowing from partner systems into NVIDIA’s data warehouses. Use data analytics tools to identify anomalies or control gaps. - Reporting & Remediation: Draft clear, impactful, and actionable audit reports for executive leadership. Track remediation efforts to ensure identified risks are effectively mitigated by business owners. What We Need To See: - Bachelor’s degree in Management Information Systems, Computer Science, Cybersecurity, Supply Chain Management, or a related technical field (or equivalent experience). - 8+ years of experience in IT Audit, IT Security, or Tech Risk Management, preferably within high-tech/semiconductor manufacturing companies. - Domain Expertise: Deep understanding of automated manufacturing environments, supply chain logistics, and B2B integration technologies (e.g., EDI, APIs, SFTP). - Infrastructure & Network Audit Expertise: Solid hands-on exposure or practical familiarity with Windows/Unix server administration, virtualization, and enterprise storage systems. Ability to evaluate core networking layouts — specifically TCP/IP routing, firewall policy configurations, and common protocols (DNS, DHCP, HTTPS, SSH) — to independently verify system security and compliance controls. - Technical Proficiencies: Familiarity with Shop Floor Control and Manufacturing Execution Systems (MES). Strong knowledge of cloud security (AWS/Azure), identity and access management (IAM). - Certifications: Professional certification such as CISA (Certified Information Systems Auditor) or CISSP (Certified Information Systems Security Professional) is highly preferred. - Communication: Exceptional verbal and written communication skills, with the ability to articulate complex technical risks to non-technical business leaders and external vendors. - Travel: Ability to travel domestically and internationally (up to 15-20%) to conduct on-site partner assessments when required. Ways To Stand Out From The Crowd: - Hands-on experience with data analytics and visualization tools (e.g., SQL, Python, Tableau, or Power BI) to automate audit testing. - A proven track record of auditing intellectual property (IP) protection controls in a collaborative engineering or manufacturing environment. - Ability to drive and engage third-party IT teams to complete tasks remotely in accordance with NVIDIA IT standards. Energetic, proactive, and possessing a strong “can-do” attitude; comfortable communicating with both IT and non-IT personnel NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join us! NVIDIA is redefining what’s possible with AI, and our Relational Foundation Model team is at the forefront of that mission. We’re building a single, unified foundation model that understands the structure and relationships within any relational database or heterogeneous graph — a fundamentally new approach to enterprise AI. As an engineer on this team, you won’t just be fine-tuning existing models; you’ll be designing and experimenting with novel Transformer and GNN architectures that generalize across diverse relational schemas. Your work will directly impact real-world applications spanning recommendation systems, demand forecasting, fraud detection, and predictive maintenance — all powered by one extensible model. You’ll collaborate closely with researchers and engineers across the full ML lifecycle, from architecture exploration and large-scale training to post-training optimization and inference acceleration. This is a rare opportunity to contribute to foundational research that ships into production and shapes the modern data stack. If you’re excited about graph learning, relational reasoning, and building AI systems that go far beyond single-table benchmarks, this is the team for you. What you’ll be doing: - Collaborate with researchers/engineers to enhance our Transformer and GNN-based models to operate seamlessly over any relational schema and heterogeneous graph. - Gain hands-on experience with high-impact use cases such as forecasting, entity matching, customer retention and fraud detection – all built on top of a single, extensible foundation model. - Leverage your knowledge in ML and AI to tackle real challenges while contributing to scalable and adaptable solutions that push the boundaries of what’s possible. - Work may span the full lifecycle of modern ML systems: from architecture design/training to post-training optimization and inference acceleration. - You will contribute to our next generation of the Relational Foundation Model. What we need to see: - MS or PhD in Machine Learning, Computer Science, or equivalent program - Proficiency in Python and deep learning frameworks, such as PyTorch - At least 8 years of research experience in designing ML algorithm solutions - Practical experience in using Predictive Models in Real World Applications Ways to stand out from the crowd: - Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

NVIDIA is looking for an experienced GPU and network systems Solutions Architect & Engineer. Do you want to be part of a team that brings new Artificial Intelligence (AI) hardware and software technologies to production in customer data centers? As part of the NVIDIA SA organization, you will be driving deployment of our end-to-end technology solutions integration at some of NVIDIA's most strategic technology customers, as well as offering recommendations to business and engineering teams on our product roadmap. What you will be doing: - Working with NVIDIA AI Native and Consumer Internet customers on large data center GPU server and networking system deployments as Solution Architect Engineer. Guide customer discussions on network design, compute/storage and support bring up of server/network/cluster deployments. You will need to visit customer data center during bring up phase. - Demonstrate subject matter expertise in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers. Bring customer-specific requirements to product teams to guide product roadmap features. - Identify new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications. Work closely with the GPU/Network Systems Engineering, Product management and Sales teams - Work as customer trusted advisor conducting regular technical customer meetings for product roadmap, cluster issues debug, feature discussions and introduction to new technology solutions - Build custom product demonstrations and POCs for solutions that address critical business needs of our customers - Analyze and debug compute/network configuration, performance issues to deliver performant clusters What we need to see: - BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience. - This role is for an individual with the motivation and skills to drive the data center engineering process. Ideal candidate has 6+ years of Systems/Solution Engineering (or similar Engineering roles) experience - System level expertise of CPU/GPU server architecture, NICs, Linux, system software and kernel drivers - Experience with networking switches for Ethernet/Infiniband, and Data Center infrastructure (power/cooling) - Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes - Effective time management and capable of balancing multiple tasks - Strong verbal/written communication skills and share your ideas/code clearly through documents, presentation etc Ways to stand out from the crowd: - External customer facing background - Experience with bringup and deployment of large clusters - Systems engineering, coding, and debugging skills including experience with C/C++, Linux kernel and drivers - Hands-on experience with NVIDIA GPU systems/SDKs (e.g. CUDA), NVIDIA Networking technologies (e.g. NICs, RoCE, InfiniBand), and/or ARM CPU solutions - Familiarity with virtualization technology concepts We make extensive use of conferencing tools, but occasional (20%) travel is required for on-site visit to customers and industry events. We are open to remote work location and look forward to have you join our team! NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NALASAHiring Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s Worldwide Field Operations (WWFO) team is seeking a Solutions Architect with deep expertise in Diffusion Models. You will work as the primary technical specialist for selected NVIDIA customers. Your task is to help our customers and make their solutions more efficient, usable or economic by driving adoption of state of the art compute and software platforms. A key part of this role involves close collaboration with a wide range of team members including developers, data scientists, IT managers, and senior executives. The ideal candidate is an experienced AI specialist with a deep understanding of generative AI diffusion models, data selection and their training. What you will be doing: - Serve as the primary technical expert between NVIDIA and our ecosystem. - Partner externally with developers, researchers, technology specialists, IT professionals and executives to facilitate the integration of NVIDIA technology - Partner internally with engineering, product and research What we need to see: - Deep expertise and hands-on in AI/Deep Learning specifically with diffusion networks and the intersection of image/video/text processing - MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields. - Excellent verbal, written communication, and technical presentation skills in English. - 6+ years' work or research experience with Python/ C++ / other software development Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer www.nvidiabenefits.com/ NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a Solutions Architect with a performance engineering background who can help our most sophisticated Autonomous Vehicles and Robotics customers accelerate Physical AI workloads using NVIDIA's full-stack technologies! As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of Autonomous Vehicles. We dive deep into customer projects to solve performance bottlenecks. We use insights from workloads to guide next-generation NVIDIA hardware and software. If you are driven by innovation and ambition, this is the team for you! What you'll be doing: - Engaging directly with key AV application engineers to understand the current and future problems they are solving. You will develop and improve fundamental parallel algorithms and data structures. You will provide efficient solutions using GPUs through library development and direct application contributions. - Collaborating closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the build of next-generation architectures, software platforms, and programming models. - Engaging in deep optimization of high-performance operators, involving but not limited to GPU kernel optimization, instruction-level tuning, and compiler optimization. These optimizations will directly support customers to use NVIDIA libraries such as cuDNN, cuBLAS, and CUTLASS and Open- source libs like DeepGEMM, FlashMLA, FlashAttention, Flashinfer, etc. - Improving communication for Physical AI-related distributed transformer workloads by employing communication tools developed by NVIDIA. These include NCCL, NCCL GIN, and NVSHMEM, as well as open-source solutions like DeepEP and NCCL EP. This demands in-depth study of interconnect topologies (NVLINK) and network protocols (InfiniBand/RoCE) to develop efficient data transfer strategies alongside techniques enabling compute-communication overlap. What we need to see: - BSc/MSc/PhD or equivalent experience in Computer Science, Electrical Engineering, Physics, Mathematics, or a related technical field. - 8+ years of hands-on validated ML/DL performance engineering experience with focus on improving GPU compute efficiency of training and inferencing workloads. - Experience with C, C++, or Python and proficiency with Linux. - Solid understanding of software development, programming techniques, and algorithms. - Strong mathematical fundamentals, including linear algebra and numerical methods. - Background in parallel programming and high-performance computing, with extensive knowledge of parallel architectures and methods for performance analysis and tuning. Experience in GPU programming is desirable. - Experience in distributed communication optimization is highly helpful. This involves familiarity with remote direct memory access, GPU interconnects, collective communication algorithms, and associated open-source libraries used in large-scale model training and inference. - Effective verbal/written communication, and technical presentation skills. Ability to communicate your ideas/code clearly through blog posts, GitHub, ppt. Ways to stand out from the crowd: - Prior experience in writing CUDA kernels, and experience with Nsight System and Nsight Compute. - Experience in comprehensive evaluation and improvement of full-stack systems within at least one of these areas: LLM and HPC. Having expertise ranging from operator-level through framework-level to algorithm-level optimization is strongly preferred. - Proven software engineering fundamentals and system architecture thinking, with the ability to build modules and lead engineering approaches in complex systems. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ NALASAHiring Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI—the next era of computing—with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” Are you willing to challenge yourself and build phenomenal software alongside some of the smartest people in the world? Join us at the forefront of technological advancement. We’re hiring a Senior Backend/Platform Engineer to build and maintain the core infrastructure behind NVIDIA Brev. You’ll develop reliable cloud services, control planes, and execution environments that enable developers to access accelerated computing infrastructure across clouds. This is a high-impact role for an engineer who enjoys solving complex infrastructure problems, operating production systems, and building platforms that other engineers depend on! What You’ll Be Doing: - Design, build, and operate production backend services and infrastructure in Go - Develop platform capabilities for provisioning, managing, and executing workloads across cloud environments - Build reliable control planes, APIs, schedulers, and infrastructure automation - Work deeply with Linux, Kubernetes, containers, networking, and public cloud infrastructure - Own systems throughout their lifecycle, including architecture, implementation, deployment, observability, incident response, and continuous improvement - Solve distributed-systems challenges involving state, concurrency, multi-tenancy, workload isolation, failure recovery, and scalability - Build infrastructure and platform primitives used by other engineers and developer-facing products , and e stablish best practices for system design, code quality, testing, reliability, and production operations - Collaborate across engineering and product teams to translate complex infrastructure requirements into simple, dependable developer experiences What We Need to See: - B.S. degree or equivalent experience - 8+ years of relevant software engineering experience, with flexibility for exceptional candidates - Strong professional experience developing production systems in Go , Linux systems knowledge and the ability to debug across system layers - Strong networking fundamentals, including TCP/IP, DNS, routing, proxies, VPNs, and load balancing - Hands-on experience with Kubernetes and containerized workloads, and building infrastructure on AWS, GCP, or Azure - Backend or platform engineering experience with production systems  and s trong distributed-systems fundamentals, including consistency, fault tolerance, concurrency, and failure handling - Experience building infrastructure, developer platforms, cloud services, or shared systems that other engineers depend on - A track record of owning reliability and operational outcomes in addition to feature delivery Ways to Stand Out from the Crowd: - Experience with Temporal or another durable workflow orchestration system - Experience designing multi-tenant platforms, control planes, or schedulers - Knowledge of VM lifecycle management, remote execution environments, or sandbox and isolation technologies - Experience with observability, reliability engineering, capacity planning, or infrastructure automation  and building AI agent platforms or developer execution environments - Experience building and operating GPU infrastructure, including GPU provisioning, scheduling, orchestration, or workload management NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and establish teams with the most thoughtful people in the world. We are looking for an excellent Senior Engineering Manager to lead a large firmware engineering organization delivering end-to-end manageability firmware for NVIDIA's next generation Data Center Compute Systems. This role owns HGX product line and  OpenBMC-based management firmware and MCU firmware components in data center platforms, including architecture, execution, quality, reliability, telemetry, and customer readiness. We are seeking an experienced senior leader with strong technical depth, broad system perspective, and a proven ability to lead large teams through complex product cycles. This role is onsite in Santa Clara, CA, USA. If you're creative and autonomous, we want to hear from you! What you'll be doing: - Lead a large firmware engineering organization delivering OpenBMC based firmware and MCU firmware for next-generation Data Center Compute Systems. - Own HGX platform as a lead for Firmware and System software readiness working across the organization. - Define and drive the long-term firmware roadmap, balancing architectural innovation with product execution and delivery milestones. - Drive architecture strategy across BMC, MCU, platform software, manageability, health management, and data center firmware interfaces. - Lead execution across multiple programs, coordinating priorities, hiring, managing cross component dependencies, and delivery commitments across a large engineering team. - Collaborate with data center architects, cloud customers, senior stakeholders, and cross-functional teams to define requirements, scope implementation, and deliver at Speed of Light. - Partner with hardware, systems, security, validation, manufacturing, field, and customer engineering teams to ensure scalable manageability architecture across data center products. - Manage customer and executive escalations for complex firmware, platform, and deployment issues. - Build, mentor, and grow a high-performing engineering organization with strong technical leadership, execution discipline, and quality culture. What we need to see: - BS, MS, or PhD in EE/CS or related field of education or equivalent experience. - 12+ overall years of proven experience in server firmware, BMC/OpenBMC, MCU firmware, platform software, or data center systems. - 6+ years of experience managing software/firmware engineering teams. - Strong technical leadership in data center system architecture, server manageability, telemetry, health management, and reliability at scale. - Proven record delivering production firmware for large data centers with strong quality, debug, and operational discipline. - Experience leading architecture and execution across multiple programs, cross-functional teams, and customer-facing deliverables. - Strong understanding of firmware development lifecycle, validation, release management, issue triage, and production support. - Excellent communication skills, strong work ethic, sound judgment, and the ability to align teams through complex technical and business tradeoffs. Ways to stand out from the crowd: - Experience leading large distributed engineering organizations, including multi-team execution and senior technical leaders. - High level of ownership to deliver products working across matric organization, having done that for a couple of products. Having mindset bucks stop at me. - Hands-on experience with BMC firmware/software stack, MCU firmware, C/C++, Python, and debugging server platform. Expertise with OOB management DMTF protocols and standards such as MCTP, PLDM, SPDM, and Redfish. - Experience with Embedded Linux, FreeRTOS, Yocto/BitBake, Git, Perforce, Jira, and modern firmware CI/CD practices. - Proven ability to drive complex architecture, quality, reliability, and customer escalation work across 25+ engineers or similarly large engineering teams. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come, join our Data center server systems team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a (Senior) Software Engineer for Autonomous Vehicles supporting Calibration. We are seeking software engineers with interests in computer vision, calibration, egomotion, sensor fusion, handling large and complex software systems on automotive and embedded platforms to work as part of NVIDIA’s autonomous vehicles team. You will be supporting the calibration team with development and validation of the calibration / egomotion algorithms on vehicles, maintaining and productizing existing calibration approaches, supporting infrastructure in first level triaging and monitoring calibration performance across the fleet. You will be working with NVIDIA's OEM partners to help bring up existing and new calibration-related features on prototype and pilot production vehicles. What you will be doing: - Develop new approaches and implement improvements to existing algorithms for sensor calibration for ADAS using both classical and deep learning methods. - Work with large amounts of real and synthetic data to evaluate and improve the algorithmic and computational performance of sensor calibration. - Develop and optimize software architecture and frameworks for real-world performance towards internal and external customer requirements. - Work with a variety of sensor modalities: camera, LIDAR, radar, IMU, GPS, odometry, etc. - Develop unit tests, documentation for features, evaluate quality and propose improvements and corrective actions. - Develop highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA). - Develop production code to strict quality and safety standards such as MISRA and AUTOSAR. - Develop and maintain fleet monitoring tools supporting calibration of a large vehicle fleet. - Perform in-vehicle tests and troubleshooting, mining/analyzing data and completing drive missions. - Adopt and improve calibration algorithms on existing and new vehicle variants. What we need to see: - PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Excellent C++ and Python programming skills. - General knowledge of fundamental algorithms in Robotics, Controls / Estimation and 3D Computer Vision. - Strong knowledge of programming and debugging techniques, especially for automotive / robotics systems. - Great communication and analytical skills including contributing critical and constructive design and code review. - Comfort with local/remote Linux machines, git, build systems. - Self-motivation and a great teammate. Ways to stand out from the crowd: - Experience with data-parallel and/or CUDA programming. - Experience with performance analysis, optimizations and benchmarking. - Background with automotive systems, notably ADAS applications. - Deep experience with bazel, docker, VSCode plugins, code analysis/QoL tools. - Proven track record of working on calibration related projects, i.e. developing new calibration algorithms Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: - Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. - Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack - Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available - Triage and root-cause performance issues reported by our customers - Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information - Collaborate with a very dynamic team across multiple time zones What we need to see: - M.S. (or equivalent experience) or PhD in Computer Science, or related field with relevant performance engineering and HPC experience - 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM) - Experience conducting performance benchmarking and triage on large scale HPC clusters - Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) - Implement micro-benchmarks in C/C++, read and modify the code base when required - Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python - Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker) - Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: - Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control - Experience debugging network issues in large scale deployments - Familiarity with CUDA programming and/or GPUs - Experience with Deep Learning Frameworks such PyTorch, TensorFlow Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA GH200 superchip provides performance and productivity required for strong scaling for HPC and generative AI workload. Scale out is inherent to design of this massive superchip. We are looking for expert engineers to come and help design rack level solutions for next generation scaling AI supercomputing platforms. We are looking for a strong technical architect to own end to end manageability architecture for these products in data centers. You will work with various component leads internally and externally, drive customer use cases, align architecture with customer requirements and release best products to market. Join us at the forefront of technological advancement. What you’ll be doing: - Drive server management for large clusters and data centers deploying GPUs and Grace solution from Nvidia. - Work with data center architects and cloud customers to narrow down on requirements for implementation to ensure speed of light product development. - Work with internal teams to make sure requirements are designed and implemented in right way with each firmware and software module - Collaborate with other leads to design & build data center health management workflow. - Drive reliability and optimization in firmware architecture from a data center view point. - Work closely with cluster bring up team and resolve issues at Speed of Light - Own firmware delivered to data centers in terms of quality, reliability and telemetry performance. What we need to see: - 15+ years of relevant experience working on server firmware (BMC) and platform software development - BS, MS, or PhD in EE/CS or related field of education or equivalent experience - Hands on experience with data center health management workflow. Proven record of delivering server firmware for large data centers.. - Strong knowledge of data center management, server architecture and server manageability in data centers and strong and demonstrable skill in C/C++ and Python - Experience programming and debugging skills for server platforms. - Experience in SCM (e.g. Git, Perforce) and project management tools like Jira. - You should possess excellent written and oral communication skills, good work ethics, high sense of team-work, love to produce quality work and commitment to finish your tasks every single day. - You are a self-starter who loves to find creative solutions to complicated problems and hands on with coding. Ways to stand out from the crowd: - Hands on experience with data center health management - Hands on with x86 or ARM system architecture. - Proven technical leaders to drive large complex problem with 50+ engineers working NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 6, and 320,000 USD - 488,750 USD for Level 7. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and form teams with the smartest people in the world. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. What you’ll be doing: - Design and implement Microcontroller Firmware for GPU Server platforms, focusing on but not limited to ARM M-class microcontrollers. - Develop C/C++ server manageability features in an RTOS embedded-optimized environment. - Perform hands-on work with microcontroller firmware bring-up, debugging, performance analysis, and coding manageability features for NVIDIA’s Server platforms. - Develop embedded management software to enable reporting and connectivity between server management devices. - Implement register-based communication and DMTF standard messaging protocols for seamless interaction between BMC, GPUs, switches, memory, I/O expanders, sensors, and local microcontroller peripherals. - Design a highly portable microcontroller framework that will be implemented across a wide variety of server management subsystems. Develop and review code, write and review design documents, and collaborate with team members to meet product requirements. - Instrument code for maximum coverage, automate unit tests, maintain detailed test case reports, and provide software quality reports based on static analysis, code coverage, and microcontroller load. - Collaborate with security and hardware teams to ensure code aligns with security goals and influence hardware design and architecture review. Develop performance-optimized active monitoring BMC solutions using DMTF Standards such as MCTP, Redfish, SPDM, and PLDM specifications. What we need to see: - A Bachelor of Science Degree (or higher) in Electrical Engineering or Computer Science or equivalent experience. - 12+ years of experience in low level microcontroller Firmware development on embedded microcontrollers using Zephyr or FreeRTOS - Demonstrated experience in developing BMC and/or microcontroller firmware for managing CPU, GPU, Network and Storage Devices. - Experience with the following embedded interfaces - USB and I3C. Sound experience working with ARM Integrated Development Environments (IDE), debuggers, logic and protocol analyzers, and oscilloscopes. - A deep understanding of interrupt schemes, multi-threading, DMA, memory management, and working in resource restricted embedded environments. - Strong embedded programming and scripting skills using C/C++, Bash, Python, Go, etc. - Experience reviewing and using hardware schematics, reference manuals, and datasheets for embedded development. - Expertise working with server manageability protocols such as MCTP, PLDM, SPDM, SMBUS, and OCP recovery. - Solid understanding of Linux fundamentals, various distributions, packages, upgrade mechanisms, and image building/deployment. Ways to stand out from the crowd: - Hands on background working with microcontroller embedded firmware development and OOB management - Hands-on experience implementing MCTP stack in embedded environments or FPGA. Contributor to industry groups like Open Compute, OpenBMC, DMTF and open source. - Expertise in system software and platform security for x86/ARM based Rack/Blade server systems. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are currently seeking a Senior MEP / Datacenter Infrastructure Engineer to join our SA team. At NVIDIA, we are leading the AI computing revolution, delivering deep learning and high‑performance computing solutions that power many of the world’s largest and fastest data centers and supercomputers. As a member of our team, you will play a vital role in planning, designing, and deploying AI/HPC data center infrastructure with a strong focus on power, cooling, and telemetry/control systems. If you have a strong passion for mission‑critical facilities, data center MEP design, and a successful history of engaging with customers and partners on complex infrastructure deployments, this is an excellent opportunity to make a substantial contribution. What you’ll be doing: - Lead end‑to‑end planning and deployment of AI/HPC data centers, from concept and reference design through construction, commissioning, and go‑live, ensuring infrastructure aligns with NVIDIA reference architectures and operational requirements. - Collaborate with product and engineering teams to understand NVIDIA’s guidance for data center infrastructure, including power distribution, liquid/air cooling, controls and monitoring, and network/cabling architecture, and translate this rapidly into robust, scalable customer designs. - Review and evaluate customer and partner design packages (architectural, electrical, mechanical, controls), ensuring consistency with NVIDIA reference architectures, industry standards, and regulatory requirements, and provide recommendations to improve performance, scalability, cost‑effectiveness, and sustainability. - Develop and implement comprehensive pre‑deployment audit plans to assess the readiness, reliability, and efficiency of data center infrastructure components prior to AI/HPC cluster deployment, identifying risks and mitigation actions early. - Oversee construction, integration, and bring‑up activities, working closely with contractors, OEMs, service providers, and customers to resolve infrastructure issues and ensure on‑time, high‑quality delivery. - Establish and drive quality assurance and commissioning processes for power systems, liquid/air cooling systems, rack/server power and cooling integration, telemetry, and control systems to validate functionality and performance against design specifications and benchmarks. - Act as the key liaison and domain expert for customers and partners on all data center infrastructure topics, facilitating productive technical discussions and ensuring clear alignment from planning through steady‑state operations. - Develop and sustain a strong ecosystem of design firms, contractors, integrators, and service providers to enable rapid, reliable deployment of NVIDIA solutions globally. - Mentor and guide Infra SA team members and partner engineering teams, sharing best practices in MEP design, data center operations, and deployment methodologies to ensure overall program success. - Drive continuous improvement initiatives across infrastructure design and processes, identifying opportunities to increase reliability, resilience, efficiency, and automation in AI/HPC data centers. What we need to see: - Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field; an advanced degree, equivalent experience, or relevant certifications is preferred. - 8+ years of overall experience in enterprise and/or hyperscale data centers with a focus on MEP design, construction, and deployment for high‑density AI/HPC or mission‑critical environments. - Proven experience in data center engineering, operations, or infrastructure management roles, with responsibility for large‑scale deployments and cross‑functional coordination. - Strong technical knowledge of data center systems, including power distribution (UPS, switchgear, PDUs, rack power), liquid/air cooling (chillers, CDU, CRAH/CRAC, direct‑to‑chip or immersion), rack/server mechanical and power integration, and structured cabling for high‑density deployments. - Demonstrated technical and project leadership in fluid, rapidly changing environments, with the ability to drive complex programs from design through commissioning and hand‑off. - Excellent analytical and problem‑solving skills, with a keen attention to detail and a strong commitment to quality and operational excellence. - Effective communication and interpersonal skills, with the ability to engage expertly with diverse stakeholders including customers, partners, contractors, and internal engineering teams, and to lead productive technical discussions. - Strong organization and time‑management capabilities, able to plan, schedule, and coordinate multiple infrastructure projects and tasks to meet or exceed agreed timelines. - Willingness to travel up to customer sites, partner facilities, and NVIDIA data center locations as required. Relevant certifications - BICSI - CNCDP - FOA Data Center – CFOS/DC (Certified Fiber Optics Specialist, Datacenter) Ways to stand out from the crowd - Experience with data center operations processes, safety practices, and security measures in enterprise or hyperscale environments. - Solid understanding of the full data center infrastructure stack, from building shell and core through power, cooling, racks, cabling, and monitoring/controls for AI/HPC platforms. - Background working closely with server and rack manufacturers, integrators, and colocation providers on high‑density deployments. - Outstanding interpersonal skills, with a track record of building long‑term relationships with customers, partners, and internal stakeholders and serving as a trusted technical advisor.

NVIDIA is developing GPU and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to analyze deep learning performance on different hardware and software architecture and make a significant impact in a dynamic technology focused company What you’ll be doing : - Analyze performance of various deep learning workloads on different architectures - Identify architecture and software performance bottlenecks - Explore new features and system configurations to achieve better performance and energy efficiency What we need to see: - BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,) - 3+ years of working experience in relevant directions (e.g., hardware system, datacenter hardware, LLM workloads on data center) will be a plus - Be familiar with GPU or accelerator-based deep learning platform and software stack - A strong background in computer architecture - Experience on system architecture design and performance optimization - Familiar with machine learning and deep learning frameworks

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. NVIDIA is looking for a Manager of Solution Architecture to lead NVIDIA Infrastructure Specialist Team, Continuous bringup and optimization. Academic and commercial groups around the world are using NVIDIA products to redefine deep learning and data analytics, and to power data centers. We are building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What you'll be doing: - Lead a team dedicated to consulting, optimizing, and improving the resiliency of customer AI factory infrastructures, ensuring high service quality and operational perfection. - Drive hands-on infrastructure analysis and tuning of complex GPU-accelerated systems, AI workloads, and datacenter environments, identifying areas for efficiency gains and operational improvements. - Work closely with internal teams (Engineering, Product, Sales) and customer collaborators to align infrastructure strategies with business goals, enabling smooth, scalable AI deployments. - Act as a technical authority on NVIDIA GPU, CPU and networking technologies, supporting customer discussions, architecture reviews. - Establishing and evolving optimization and monitoring methodologies, using analytics and tooling to detect bottlenecks, reduce downtime, and ensure system health at scale. - Participate in customer-facing engagements, including roadmap sessions, post-deployment reviews, and incident retrospectives, helping to craft the customer experience and influence NVIDIA’s infrastructure strategy. What we need to see: - Over 4 years leading teams and 8+ overall years in service operations in large data centers, focusing on infrastructure performance. - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field, with shown technical leadership in data center, server, and network operations. - Proficiency in both Japanese and English, demonstrating clear communication of technical topics across multicultural teams and with customers. - Deep expertise in data center architecture and operations, including servers, GPUs, NICs, networking topologies, storage systems, and Linux-based environments. - Strong analytical, solving problems, and decision-making skills, capable of identifying root causes, driving continuous improvement, and delivering resilient technical solutions. - Strong communication, time management, and organizational skills, along with experience in leading complex projects, guiding technical teams, and meeting important metrics. Ways to stand out from the crowd: - Deep familiarity with AI infrastructure and workflows, including training/inference pipelines, MLOps/DevOps tools, containerization (Docker, Kubernetes), and large-scale system deployments. - Knowledge of data center infrastructure operations, including safety, security, environmental controls, and standard operating procedures. - Strong interpersonal and collaboration skills, with the ability to lead discussions, influence outcomes, and build positive relationships with both internal and external collaborators. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you!

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. As a key player in the AI revolution, NVIDIA is pushing the boundaries of what's possible in accelerated computing. We are seeking an exceptionally dedicated LLM Reinforcement Learning Framework Engineer to join our ambitious team. This role is vital in advancing our large language model (LLM) capabilities, particularly in improving reasoning abilities for math, coding, and agentic AI. Join us and contribute to groundbreaking innovations that will craft the future of computing! What you’ll be doing: - Developing and deploying reinforcement learning algorithms for LLM post‑training to improve reasoning and alignment. - Integrating RL components into NVIDIA’s LLM training and serving stack with a cross‑functional team of engineers and researchers. - Crafting and running experiments, evaluations, and debugging workflows to ensure robustness, scalability, and reliability in production. What we need to see: - Strong Python programming skills with production‑quality PyTorch experience in multi‑GPU and distributed training environments. - Hands‑on experience with modern LLM frameworks such as NeMo RL, Megatron‑LM, DeepSpeed, vLLM, TensorRT‑LLM, or similar is a big plus. - Practical experience with reinforcement learning applied to LLMs or large‑scale sequence models. - Familiarity with async and distributed orchestration (e.g., asyncio, torch.distributed, Ray, or equivalent). - 3+ years of relevant industry or research experience, and BS/MS (or equivalent) in CS, CE, EE, or a related field. - Solid foundations in probability, optimization, statistics, and deep learning. - Understanding of GPU architecture and performance optimization is a strong plus. - Strong problem‑solving, debugging, and collaboration skills, with a passion for innovation and delivering industry‑leading AI solutions. Join us at NVIDIA and help build the next generation of reasoning‑capable LLMs that make a lasting impact on the world! Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is looking for a passionate, world-class computer scientist s and engineers to work in its Compute Developer Technology ( DevTech ) team.  DevTech is an elite team bridging customer requirements and NVIDIA solutions. Inside this team, you will conquer engineering and applied research challenges originated from real-world use cases together with talented, skilled and warm-hearted teammates. All talents of different backgrounds are welcome! We don't assume you know everything about GPU and CUDA. Especially, if you consider yourself an excellent C++ engineer and really love programming, please do submit your resume! What you'll be doing: - Research and develop cutting-edge techniques in deep learning, machine learning, HPC (High Performance Computing), graphs and data analytics, and perform in-depth analysis and optimization to ensure the best performance on NVIDIA current- and next-generation accelerated computing platform, including GPU, CPU and DPU. - Work directly with key customers to understand the current and future problems they are solving and optimize their workloads to maximize performance on our platform. - Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to design and develop next-generation architectures, software platforms, and programming models. What we need to see: - MS or PhD from university in engineering or computer science or related disciplines. - 2+ years working experience - Strong knowledge of C/C++, software design, programming techniques, or AI algorithms and system. - Experience with accelerated computing, ideally CUDA C/C++/Python. - Good communication and problem-solving skills. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and talented people on the planet working with us and our engineering teams are expanding fast. If you're a creative and autonomous computer scientist with a genuine passion for parallel computing, we want to hear from you.

We are now looking for a Senior Formal Verification Engineer for GPU Kernels! Modern AI performance relies on highly optimized GPU kernels — performance-critical code where bugs can be hard to catch and expensive to miss. NVIDIA's Deep Learning Safety Team is hiring engineers to build the verification tools that prove these kernels behave correctly, enabling their deployment in a large range of environments, including safety-critical systems. The mission is to design and develop scalable verification tools for GPU kernels. You will design and implement new verification approaches that can handle the massive concurrency and complex memory model of the latest GPU architectures. Formal methods alone cannot scale to modern GPU kernels, and AI alone cannot offer safety guarantees — the team's bet is that the combination can, and you will help build it. Join the team supporting compiler and kernel developers for safe autonomous driving. What you'll be doing: In this role, you will be responsible for developing and delivering verification tools for GPU kernels. The scope of these efforts ranges from developing new algorithms to evaluating them, from building tools to automating workflows, from joining architecture discussion to learning the latest technologies from the research community. The AI + formal methods intersection is an active research area — expect to read papers, prototype ideas from them, and contribute back where it makes sense. - Design and develop robust and scalable verification tools for GPU kernels. - Integrate your work in production pipelines to support kernel and compiler developers. - Integrate AI into formal verification workflows, build agents to automate verification tasks (formalization of specifications, bug fixing, root cause analysis) - Participate in a high-energy and dynamic company culture to develop innovative software and hardware products and practice hardware-software co-design. What we need to see: - MS or PhD in Computer Science, Compute Engineering or equivalent experience. - 6+ years of relevant work experience. - Formal methods experience: symbolic execution, SMT solving, interactive theorem proving, or model checking. - Strong programming skills in C/C++ or Rust, experience in SCM (e.g., Git) and build systems (e.g., Make, CMake). - The ability to work independently, define project goals and scope, and lead your own development effort Ways to stand out from the crowd: - Knowledge of CPU and/or GPU architecture. CUDA or OpenCL experience is a plus. - Background in the formalization of weak memory models. - Experience in the verification of concurrent software. - Experience building LLM agents with tool use and multi-step reasoning, or with neurosymbolic approaches and LLM-assisted theorem proving. This is an opportunity to have a wide impact at NVIDIA by improving development velocity across our many software projects. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 27, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

An applied research team within NVIDIA’s Networking Systems & Software Architecture group is solving some of AI’s hardest infrastructure problems. The team builds systems-level software that moves data between GPUs, nodes, and storage at the speed modern AI demands—spanning low-level transport optimization, hardware-software co-design, and communication frameworks that plug directly into production AI stacks. The team's charter expands into emerging domains including quantum computing interconnects. This Principal Architect role leads the research agenda and architectural direction for how NVIDIA’s AI systems communicate at scale—across GPUs, DPUs, NICs, and heterogeneous storage. It requires someone who defines project scope from scratch, publishes original work, and translates research breakthroughs into production-grade software that ships industry-wide! What you will be doing: - Setting the long-term technical vision for distributed AI communication systems—GPU-to-GPU, GPU-to-storage, and cross-node data movement. - Conducting original research and prototyping next-generation networking solutions over RDMA, NVLink, and GPUDirect. - Driving hardware-software co-optimization with GPU, DPU, NIC, and network switch. Investigating fundamental bottlenecks in communication runtimes for large-scale AI workloads (KV cache transfer, disaggregated prefill/decode, model parallelism). - Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM. - Publishing findings, representing NVIDIA in industry forums and standards bodies, and mentoring senior engineers across the organization. What we need to see: - 15+ years in systems software and/or networking with deep expertise in high-performance networking (InfiniBand, RoCE, RDMA, NVLink), communication libraries (e.g. NIXL, NCCL, UCX, MPI, NVSHMEM), and GPU accelerated systems, with track record of defining and delivering complex, cross-team technical initiatives from research concept to production. - MS, PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field. - Deep understanding of computer architecture, memory hierarchies, DMA engines, and OS-level networking. - Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns. - Proficiency in programming languages such as C, C++, Rust and Python. Ways to stand out from the crowd: - Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. - CUDA programming and NVIDIA GPU architecture expertise. - Proved experience influencing product strategy and technical roadmap at a senior level. - Major open-source contributions. With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we’d love to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 27, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking exceptional machine learning engineers to join our world-class robotics initiatives focused on humanoid loco-manipulation. As part of the Isaac Loco-Manipulation team, you’ll collaborate with industry-leading experts, contribute to robotics foundation models including GR00T and Cosmos, and help define the future of humanoid robot capabilities. We are looking for strategic, ambitious, and creative individuals passionate about advancing the boundaries of robotics.This is demanding, cross-disciplinary work at the intersection of cutting-edge research and rigorous engineering. What you'll be doing: - Collaborate with researchers and engineers to define and execute projects in humanoid robotics loco-manipulation and mobile manipulation areas. - Contribute to the development and advancement of GR00T and Cosmos foundation models. - Develop reference workflows with Isaac Lab and Newton for humanoid and mobile manipulation dexterous tasks. - Advance technologies for robot learning and synthetic data generation using human videos. - Design, implement, and deploy novel algorithms for humanoid robot locomotion and manipulation in both simulated and real-world environments. - Transfer innovations into products, with deliverables including prototypes, open source software contributions, patents, and/or publications in top conferences and journals. - Drive the full development lifecycle from model and algorithm design, with sim-to-real transfer, to rigorous on-robot validation and production deployment. - Collaborate cross-functionally with teammates and partners to share best practices and advance shared goals. What we need to see: This role prioritizes candidates with proven execution bandwidth of applied research and engineering and a strong delivery track record on robotics  platforms. - PhD or Master’s degree in Robotics, Computer Science, or a related field (or equivalent experience). - 3+ years of experience working on robotics software. - Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow, and physics simulation tools like Isaac Sim/Lab or MuJoCo. - Expertise in foundation models for robotics and 3D perception. - Experience with sim-to-real and real-to-sim transfer in robotics. - Deep knowledge of robot learning, including imitation and reinforcement learning. - Hands-on experience of real robot testing, humanoid experience is preferred. - Strong software engineering fundamentals, including proficiency in C++ and Python. Ways to stand out from the crowd: - Experience learning from human video demonstrations or human-object reconstruction. - Expertise in dexterous bimanual manipulation or whole-body control. - Proven track record in robotics research, including publications in top conferences (e.g., RSS, ICRA, CoRL, NeurIPS, CVPR, ICLR). - Demonstrated technical leadership experience.

NVIDIA Israel is seeking innovative and driven Applied Researchers in the field of deep learning. We are looking for candidates with a consistent track record of research excellence; a broad perspective across the fields of artificial intelligence; and deep experience in machine learning, applied science, and computational medicine. NVIDIA is a world leader in high-performance and mobile computing technology for AI, with ambitious plans for future systems. This position offers the opportunity to have a real impact in an applied research-focused team in a dynamic company. The Applied AI Architecture group focuses on applied research. As a member of the team, you will publish your work and share code as an open source. In addition, you will join a groundbreaking initiative at the intersection of AI and biology. This collaborative project aims to develop both foundational and generative AI models, as well as agentic AI systems, redefining our understanding of complex biological systems and enabling advanced diagnostics and novel scientific insights, while strengthening NVIDIA’s Health Platform ecosystem. What You'll Be Doing: - Conceptualize, design, and implement novel deep learning architectures for biological data, with a strong focus on large-scale models such as Large Language Models (LLMs), Transformers, and State Space Models (SSMs). - Develop multimodal learning systems that integrate heterogeneous data types (e.g., clinical time-series, imaging, genomics, and text) for improved representation and prediction. - Develop both foundational and generative models and agentic AI systems, including multi-step reasoning, tool use, and autonomous decision-making capabilities. - Develop digital twin systems for healthcare, combining mechanistic models, physiological data, and AI to simulate disease progression, treatment response, and patient-specific trajectories. - Implement deep learning systems integrated with agents, enabling end-to-end workflows that combine learning, planning, and execution. - Evaluate model performance, analyze results, and iterate on designs to achieve optimal outcomes. - Apply your knowledge of distributed training to build high-quality code for training, optimizing, and deploying large-scale models, while managing complex datasets. - Collaborate closely with a diverse team of researchers, bioinformaticians, and domain experts in a highly interdisciplinary environment. What We Need to See: We are looking for individuals who demonstrate a strong foundation in deep learning and a proven ability to translate innovative ideas into practical, scalable systems. - PhD in Machine Learning, Computer Science, Engineering, or a related discipline. - 8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including LLMs, Transformers, SSMs, and/or generative models. - Experience with multimodal learning and integrating diverse data modalities is highly valued. - Experience with agentic AI frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems) is a strong advantage. - Strong expertise in distributed training, optimization, and inference. - Proven ability to lead independent research, implement robust solutions, and rigorously evaluate performance. - Track record of publications and presentations at top conferences. - Strong programming skills in Python and C++, with experience in PyTorch and/or CUDA. - Excellent communication skills and ability to thrive in a dynamic, research-driven team. Mentoring experience is a plus. Ways To Stand Out From The Crowd: - Hands-on experience building advanced AI systems, including agentic AI (RAG, tools, planning, multi-agent) and multimodal models combining vision, language, and structured/time-series data. - Proven track record optimizing large-scale ML systems, with experience in data pipelines and distributed frameworks for LLM-scale data. - Background in bioinformatics or digital biology, with experience working across interdisciplinary teams spanning research, engineering, and clinical domains. - Experience in building or implementing digital twin systems, simulation frameworks, or data-driven modeling in healthcare or related domains is a strong plus. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Reinforcement learning post-training is driving some of the most significant capability gains in AI today. It is the process that teaches a model to reason through hard problems, follow complex instructions, and act as an autonomous agent. It is also one of the hardest infrastructure challenges in the field. RL requires inference, rollout generation, and training running in a continuous loop. The rollout step is what makes it hard: the model must interact with environments, tools, and other models to produce the signal that drives learning. Coordinating actor, critic, and reward models across heterogeneous hardware at scale pushes the limits of what distributed systems can do. NVIDIA is building an RL Frameworks engineering team to develop the open-source tools and infrastructure that AI researchers and post-training teams depend on. The team spans the full software stack, from collaborating closely with the researchers and labs pushing the frontier, to contributing to RL frameworks like   VeRL ,   Miles , and   TorchTitan , to improving the distributed runtimes they depend on, including   Ray   and   Monarch . Whether your strength is working with researchers to understand and address their need optimizing deep learning frameworks, or building distributed infrastructure, we want to hear from you. Come join us to build the systems that enable the next generation of AI. What you will be doing: You will architect and build RL post-training infrastructure that scales efficiently from experimentation on a single GPU to production across thousands of nodes. This means tuning RL training-inference-rollout loops on GPUs, CPUs, and LPUs for performance where it matters, contributing to and improving the performance and usability of open-source RL frameworks, and partnering with the teams who own them. The role also spans fault tolerance, elastic scaling, and fast restarts so long-running distributed training jobs survive failures, stragglers, and resource contention. Beyond GPU-accelerated training, this work includes partnering with teams building CPU-driven rollout workloads, including tool-use, code execution, and agentic environments, supplying the systems and framework engineering needed to run them efficiently alongside GPU- or LPU-accelerated generation and GPU-accelerated training. It also means advocating for researcher and partner needs with NVIDIA's networking, math library, and compiler teams so the capabilities RL workloads require get prioritized and delivered, and working with hardware teams to take advantage of next-generation hardware capabilities in post-training workloads. What we need to see: - MS or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience) - 5+ years of professional experience in distributed systems, high-performance computing, deep learning infrastructure, or ML systems engineering - Strong proficiency in Python and C/C++ - Demonstrated experience building or contributing to large-scale distributed systems or runtime frameworks in production at a frontier AI lab, hyperscaler, or major technology company - Strong verbal and written communication skills and the ability to collaborate across organizational and geographic boundaries Depth in one or more of the following technical areas: - Reinforcement learning for LLM post-training (RLHF, PPO, GRPO, DPO, reward modeling), including how algorithms map to distributed execution and the systems challenges they create (heterogeneous placement, rollouts, environment execution, resharding between training and generation) - PyTorch internals, including distributed training primitives (FSDP, tensor parallelism, pipeline parallelism) and their composition - Kubernetes runtime internals (container lifecycle, pod scheduling, resource quotas, GPU allocation) - End-to-end distributed systems design (service boundaries, data flows, consistency models, failure modes, recovery approaches) Experience in any of the following areas is a plus: - Deep expertise in networking (NCCL, NVLink, InfiniBand), advanced multi-dimensional parallelisms (Megatron-LM, FSDP2, TP/DP/PP, MoE), or memory optimizations (quantization-aware training, mixed precision) - Experience integrating high-performance inference engines (vLLM, SGLang, TensorRT-LLM) into RL training loops for GPU-accelerated rollout - Strong background in actor- and task-based distributed programming (Ray, Monarch, or comparable systems) - Familiarity with multi-turn training, multi-agent co-evolution, or VLM post-training Ways to stand out from the crowd: - Open-source contributions to RL post-training or distributed training projects (e.g., VeRL, Miles, TorchTitan, OpenRLHF, NeMo-Aligner, DeepSpeed-Chat), including significant work on framework internals where applicable - Kubernetes work beyond routine operations (custom operators, GPU device plugins, or scheduling contributions) - Direct experience operating frontier-scale training (RL post-training at thousands of GPUs and/or large-scale LLM or multimodal pre-training) - Hands-on experience with production distributed failures at scale (stragglers, resource contention, hardware faults) Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 27, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are in search of a top-tier AI Agents applied researcher to work closely with hardware architects and software developers to develop end-to-end agentic systems that drive significant enhancements in NVIDIA's products. Our team propels generative AI forward by building and deploying agentic systems that integrate innovative LLMs with domain tools to expedite HW and SW engineering workflows at scale. What You'll Be Doing: - Build complex agentic systems featuring multi-agent coordination, long-horizon reasoning, and advanced planning frameworks. - Develop full-scale solutions, including domain-specific enterprise agents and high-performance retrieval pipelines (RAG) spanning various data sources. - Develop innovative AI flows to improve hardware and software through collaboration with various engineering roles. - Collaborate with SME's to transform rules of thumb into specific assignments, resources, cues, and guidelines. Define success measures, evaluation data, and feedback loops for agents to make a measurable difference in NVIDIA's HW and SW products. - Set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements. What We Need To See: - BSc/MSc in CS/CE or related field (or equivalent experience) - 10+ years in applied ML/AI or large-scale systems, with 3+ years crafting agentic or LLM-powered applications in production environments. - Proficient in Python; skilled in agentic frameworks, tool use, RAG pipelines, and model adaptation. - Excellence in communication and facilitation: aligning diverse collaborators, documenting decisions/assumptions, and influencing without authority. - Proactive, independent, possessing strong analytical and problem-solving abilities; adept at handling uncertainty to provide practical, gradual benefits. Ways To Stand Out From The Crowd: - Strong software development experience - Experience with data processing and storage (e.g. SQL databases, NoSQL databases). - Networking background, with knowledge of network architectures and networking concepts At the intersection of cutting-edge innovation and global impact, we have cultivated an environment where the world's most brilliant minds thrive. We offer industry-leading compensation and a culture built on excellence. If you are a high-impact applied researcher who lives for complex problem-solving and technical mastery, you belong here. We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. NVIDIA is seeking top-tier AI Compiler Engineers to drive innovation within our world-class compiler organization. In this role, you will push the boundaries of what is possible in AI performance and help build the technology that powers the next generation of computing. Join us and make a tangible impact on a global scale. What you’ll be doing: - Drive technical innovation: Participating in hands-on development focusing on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs. - Advance the state-of-the-art: Solve complex compilation problems for AI workloads (both inference and training) and successfully transition these breakthroughs into enterprise and consumer products. - Collaborate on hardware/software co-design: Partner with leading experts across our software, hardware, and research divisions to architect and co-design future silicon. - Scale AI to the datacenter: Participating in the advancement and optimization of datacenter-scale AI workload deployments. What we need to see: - BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). A PhD is strongly preferred. - Compiler Experience: 3+ years of relevant industry experience specializing in compiler optimizations, synthesis, and placement. - MLIR Knowledge: Demonstrated, hands-on experience working with MLIR. - Programming Excellence: Exceptional C/C++ and Python programming and software design skills, including rigorous debugging, performance analysis, and test design. - Team Dynamics: Strong communication and interpersonal skills, with the ability to collaborate effectively in a dynamic, fast-paced, and product-oriented environment. Ways to stand out from the crowd: - Hardware Implementation: Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures. - LLM Knowledge: Deep understanding of Large Language Model (LLM) inference and its profound implications on computer architecture. - Architecture & Design: Demonstrated understanding in the designing and architecting of comprehensive compiler frameworks from the ground up. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's technology is at the heart of the AI revolution, touching people across the planet by powering everything from self-driving cars, robotics, co-pilots, and more. Join us at the forefront of technological advancement in intelligent assistants and information retrieval. Metropolis is transforming how the physical world is perceived and understood using advanced computer vision and deep learning. Our team builds large-scale distributed Vision AI platforms that power intelligent spaces, smart cities, retail analytics, and digital twins. This role offers the opportunity to own core components of a strategic platform with high visibility and real-world impact. As a System Software Engineer for Vision AI, you will develop and optimize high-performance vision systems that turn massive streams of video, image, and 3D data into actionable insights. You will collaborate with specialists in perception, simulation, and large models to bring research into production at scale. What you’ll be doing: - Crafting and implementing high-performance Vision AI pipelines for real-time and streaming scenarios using brand-new computer vision and deep learning models. - Developing and refining large-scale distributed services responsible for processing video, image, and 3D data in both edge and cloud settings. - Developing multi-modal perception capabilities that combine 2D, 3D, and temporal information to understand complex real-world scenes. - Using simulation and synthetic data tools to build, test, and validate perception algorithms at scale. - Profiling and tuning GPU-accelerated inference pipelines to meet strict latency, efficiency, and reliability targets. - Collaborating with partner teams across product, research, and platform to translate requirements into clear technical builds and robust implementations. - Driving technical build reviews, promoting guidelines for code quality and testing, and mentoring other engineers on Vision AI systems development. What we need to see: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience. - 12+ years of professional software development experience using modern C++ (14/17/20) and Python on Linux. - Strong computer science fundamentals, including algorithms, data structures, concurrency, and distributed systems concepts. - Demonstrated expertise in computer vision and deep learning, with a history of deploying production systems in these fields. - Experience building and debugging high-performance, concurrent systems, including multi-threading, asynchronous I/O, and efficient memory management. - Proficiency working in Linux-based environments with containers and microservices, integrating AI components into scalable back-end services. - Ability to rapidly prototype vision models and pipelines, then evolve them into production-quality services. - Practical experience with PyTorch in training, fine-tuning, and deploying models for vision tasks. - Strong analytical and problem-solving skills, with a data-driven approach to performance optimization and system build. - Excellent written and verbal communication skills, with demonstrated success collaborating across time zones and functions. Ways to stand out from the crowd: - Proven experience delivering end-to-end computer vision applications in production, such as video analytics, smart cities, autonomous systems, retail analytics, industrial inspection, or digital twins. - Practical experience with GPU acceleration (such as CUDA, TensorRT, or comparable technologies) and low-level optimization for inference and pre/post-processing. - Experience in simulation and synthetic data creation employing tools such as Omniverse, Unreal Engine, Unity, or similar digital-twin platforms. - Background in vision-language models or related multi-modal AI, including integrating these models into real products. - Background in multimedia, including video-centric processing and delivery (such as codecs, video pipelines, or media frameworks) and integrating vision models into multimedia workflows. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Deep Learning, Artificial Intelligence, and Autonomous Vehicles. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Development Engineer; you will collaborate with multi-functional groups. SWQA Developer Engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA Engineer can improve productivity or optimize test plan. As a SWQA Developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What you’ll be doing: - Review product requirements and develop test matrix. - Build test plan, design test case, execute and report test progress, bugs, and results to management. - Automate test cases and assist in the architecture, crafting and implementing of test frameworks. - Manage bug lifecycle and co-work with inter-groups to drive for solutions. - In-house repro and verify customer issues/fixes. What we need to see: - BS or higher degree or equivalent experience in CS/EE/CE plus equivalent with 5+ years QA experience. - Proficient in Unix/Linux and shell/python programming skills. - Rich experience in test cases development, tests automation in API/UI and failure analysis. - Solid experience with AI development tools, including creating test cases, automating test cases, and ensuring comprehensive code coverage, among other related tasks - Good knowledge and hands-on experience in model testing and LLM benchmarking - Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc. - Excellent communicator, fluent written and verbal English. - Good teamwork with ability to work independently. Passion to learn new hardcore technology. Ways to stand out from the crowd: - Experience working with NVIDIA GPU hardware is a strong plus - Background in deep learning frameworks is a plus - Experience in parallel programming ideally CUDA/OpenCL is a plus

NVIDIA is looking for a hardworking PR storyteller and leader to help expand awareness of AI’s influence in many industries. These industries include telco, energy, retail, finance, media & entertainment, and others. Join our team at a time when the world is changing rapidly, thanks to NVIDIA advances in AI and accelerated computing.  If you are driven and have a passion for driving new technologies , then join us! What you’ll be doing: - Lead communications strategy and execution to showcase how industries and key partners are fully embracing AI to transform their businesses - Collaborate with business leaders, marketing leads and industry partners to develop and tell compelling stories to the media - Engage in proactive storytelling / media engagement about the impact of AI and accelerated computing technology across various industries - Develop key messages that resonate with external audiences - Pitch and manage stories with reporters to secure impactful press coverage - Nurture strong long-term relations with business, technology and trade media What we need to see: - 10+ overall years of PR/comms experience at leading tech companies/agencies - 5+ years of team management experience - Experience leading media relations strategy and execution in a high-stakes environment - Bachelors degree or equivalent experience. - Outstanding communication skills, including professional writing abilities and verbal communication - Proven ability to generate impactful media coverage, working with a range of reporters and subject matter areas - Ability to uplevel technical messages into compelling narratives that are understandable to audiences of all types - Demonstrate an eagerness to go above and beyond, seek out challenges, and anticipate needs before they arise - Able to think outside of launches, events and announcements to keep PR momentum going through proactive opportunities - Highly diligent with outstanding project-management skills - Creative, collaborative, and organized, with a knack for balancing multiple projects - Experience managing a small team and/or agency relationship Ways to stand out from the crowd: - Experience in AI, enterprise, and technology communications - Experience in two or more industries, and proven track record of successfully telling complex technology stories in an approachable way - Strong relationships with business and technology reporters Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 196,000 USD - 310,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 1, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can take on, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Are you passionate about working on a team that is at the cutting and bleeding edge of hardware technology? Our System Level Product Engineering team at NVIDIA works on groundbreaking innovations involving crafting creative solutions for system level diag, verification and post-silicon validation on some of the industry's most complex semiconductor chips. If you're creative and autonomous, we want to hear from you! At NVIDIA, you will have the opportunity to shape some of the most incredible products on the market today. Your work will touch every industry - from medical, to auto, to robotics and more. What you'll be doing: - As a member of our system level product development engineering group, you will be responsible to develop and improve all aspects of testing NVIDIA's state of the art GPU products. - Your duties include characterization, yield enhancement, spec validation, customer failure improvement, and addressing the production issue . - Expect to interface with other engineering groups to resolve silicon issues. - Initiate and drive process improvements and preventative actions, possibly through root cause analysis. - It is imperative that this individual always looks to improve work, products, functions and methodologies through an on-going analysis while communicating and sharing new information and methods with cross-functional team members to achieve the company goals. What we need to see: - Master's degree in Electrical Engineering - 5+ years of product engineering work experience or relevant experiences - Be self-motivated with strong technical, interpersonal, written/oral communication skills - Problem solving experience/ability - Be able to quickly become a strong contributor both as an individual and as a member of highly productive team - Skilled at collaborating with global teams. - Knowledgeable with PC architecture, AGP/PCIe busses and SDRAM/DDR/HBM is a plus Ways to stand out from the crowd: - Experience with system level testing. - Background with Perl, Python, C/C++, Windows, and Linux. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! Our team builds AI-driven software systems for circuit design, combining automation algorithms, DL models and agentic workflows to accelerate end-to-end design automation. What you'll be doing: - Work within a multi-functional team on projects involving pre-silicon and post-silicon hardware design data, circuit optimization, SPICE correlation, and AI systems for EDA/design automation. - Work on applications ranging from silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and agent flow optimization. - Translate requirements into data science, AI/ML, and agentic system problems; architect and build solutions. - Test and release models and AI systems that integrate with existing machine learning, design automation, and visualization tools within the organization. - Analyze datasets, raise and validate hypotheses, extract relevant features, and build models and self-improving workflows on top of them. - Optimize models, algorithms, and autonomous optimization systems until they reach the desired QOR. What we need to see: - Master's or PhD in Electrical or Computer Engineering, Computer Science, or Applied Mathematics (or equivalent experience). - Knowledge in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design is required. - Prior experience in Applied Math/ML/Software programming with proven ability in writing code in Python and C++. Ways to stand out from the crowd: - Experience building AI systems for EDA, design automation, or circuit design workflows. - Research or project experience in AI-driven EDA, circuit optimization, design-space exploration, or autonomous design systems. - Experience building agentic systems, autonomous optimization loops, self-improving AI systems, or production-scale AI/ML platforms. - Experience with deep learning algorithms, AI agent frameworks, and tools such as PyTorch, LangChain, or LangGraph is a definite plus. NV IDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 1, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are seeking a Senior Deep Learning Researcher for an excellent opportunity! This role provides an outstanding opportunity to engage in groundbreaking innovation and contribute to advancing diffusion-based technologies. You will work with pioneering methodologies and tools, crafting solutions that push the boundaries of AI capabilities. Joining NVIDIA means being part of a phenomenal team renowned for its inventions, such as NVIDIA Cosmos , Llama-Nemotron , Sana , and contributing to impactful work that influences various applications. We offer a collaborative environment that fosters professional growth. You will have the opportunity to collaborate with some of the brightest minds in the field, both within NVIDIA's global network and with leading companies worldwide, making this role perfect for those passionate about advancing AI technology and eager to make a significant impact on the future of the field. What you'll be doing: - Invent and build ground-breaking techniques for efficient multi-modality model creation and publish the findings in leading journals and conferences. - Combine traditional diffusion technologies with the latest and greatest LLMs. - Contribute to NVIDIA's AI enterprise software to ensure robust and scalable solutions. - Collaborate with internal and external teams worldwide to drive research and development in multi-modal learning, using different professions and resources across the company. - Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications. What we need to see: - PhD. in Computer Science, Electrical Engineering, or a closely related field, or equivalent experience. - At least 3 years of relevant research experience - Publications in prestigious conferences and journals like NeurIPS, ICLR, and CVPR - In-depth understanding and active research experience in leading generative AI techniques, with a track record of contributing to advancements in this area - Extensive experience in image and video understanding, generation, and reasoning. Ways to stand out from the crowd: - High proficiency in programming and coding - Degree from a top-tier institution or equivalent experience in a world-class industrial research group - Substantial contributions to the multi-modality or diffusion forefront of research. - Experience in research fields of LLMs. Candidates should apply with a detailed CV, publication list, and brief research statement. We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you'll be doing: As a Solutions Architect in NVIDIA AI Technology Center (NVAITC), you will be leading the way in AI research and application. You will: - Lead and mentor junior technical members, encouraging a collaborative and inclusive environment. - Collaborate with the management team to develop and implement strategic engagements and projects involving institutes of higher learning (IHLs), industry, and government, ensuring seamless delivery and implementation. - Serve as a research & engineering subject matter expert (SME), driving internal and external collaborations with academia and industry. - Serve as the technical expert for NVIDIA technologies including Omniverse, NeMo, NIMs, RAPIDS, and Deep Learning toolkits. - Play a key role in NVIDIA’s global initiative to foster accelerated AI throughout the ecosystem by facilitating and supporting workshops, symposiums, and technical sharing sessions. - Mentor collaborators, interns, and students, providing mentorship and skills training to successfully implement AI projects. - Develop NVIDIA technology-related tutorials, demos, and workshop materials, showcasing our world-class innovations. What We Need To See: - Demonstrated 5+ years of experience with NVIDIA technologies (i.e., Omniverse, NeMo, NIMs, RAPIDS, AI model training using accelerated AI compute, etc.). - Proficiency in AI research areas including Digital Twins, Synthetic Data Generation, Immersive Multimedia, and Generative AI. - A PhD or equivalent experience in Artificial Intelligence or related research domains. - A proven history of guiding and assisting research & engineering projects. - Technical mentoring experience in areas such as research/engineering projects. - Experience in AI ecosystem development and collaboration initiatives. - Proficiency in coding with Python and using AI/ML libraries such as Pytorch. - Strong knowledge of synthetic data creation, digital twins, immersive multimedia, deep learning, and machine learning methods. - Excellent time management skills, self-motivation, and the ability to work both independently and within a team. - Effective communication skills, enabling you to articulate complex concepts clearly and concisely. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with specialized expertise in training Large Language Models (LLMs) and implementing workflows based on Pretraining, Finetuning LLMs & Retrieval-Augmented Generation (RAG). As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering cutting-edge solutions that leverage the power of NVIDIA's generative AI technologies. This position requires a deep understanding of language models, particularly open source LLMs, and a strong proficiency in designing and implementing RAG-based workflows. What You Will Be Doing: - Architect end-to-end generative AI solutions with a focus on LLMs training , deployment and Agentic AI workflows. - Collaborate closely with customers to understand their language-related business challenges and design tailored solutions. - Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of LLM and Agentic AI capabilities. - Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI software. - Engage directly with customers/partners to understand their requirements and challenges. - Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and Agentic AI workflows and lead the training and optimization of Large Language Models using NVIDIA’s hardware and software platforms. - Implement strategies for efficient and effective training of LLMs to achieve optimal performance. - Design and implement RAG-based workflows to enhance content generation and information retrieval. - Work closely with customers to integrate AI Agents into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies. - Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions. What We Need To See: - Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience - 5+ years of hands-on experience in a technical AI role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs). - Proven track record of successfully deploying and optimizing LLM models for inference in production environments. - In-depth understanding of state-of-the-art language models, including but not limited to GPT, Nemotron, or similar architectures. - Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers. - Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs. - Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference. - Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. - Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences. Ways To Stand Out From The Crowd : - Experience in deploying LLM models in cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure. - Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. - Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment. - Deep understanding of GPU cluster architecture, parallel computing, and distributed computing concepts. - Hands-on experience with NVIDIA GPU technologies, and GPU cluster management and ability to design and implement scalable and efficient workflows for LLM training and inference on GPU clusters With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are seeking a highly technical Developer Relations Manager to join our team, with a focus on engaging deep collaborations with the next generation of security companies building solutions for the AI and Agentic era. In this role, you will work directly with security companies, guiding them on how to leverage NVIDIA software stacks when developing solutions to secure AI and Agentic environments and workloads. The ideal candidate brings a blend of deep technical expertise and commercial go-to-market experience, combined with a passion for developer advocacy and a talent for communicating how NVIDIA technology can solve complex, real-world challenges. What You'll Be Doing: - Serve as the trusted technical advisor, problem solver, and champion for the developer ecosystem in the AI and Agentic Security industry with cross-functional partners to drive adoption of NVIDIA technologies. - Accelerate critical workloads by demonstrating groundbreaking solutions that integrate the core NVIDIA stack into developer products, platforms, and pipelines. - Guide partners and startups through onboarding and integration with NVIDIA’s programs, fostering co-innovation and the development of next-generation solutions. - Map, track, and monitor the developer ecosystem to identify growth opportunities, inform technology roadmaps, and shape adoption strategies. - Collaborate multi-functionally with solution architects, engineering, product management, and marketing to drive developer engagement and optimize partner adoption strategies. - Represent and advocate for the partner technical needs and feedback to NVIDIA’s internal product and engineering teams, supplying actionable insights from field deployments to influence product roadmaps. What We Need to See: - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field or equivalent practical experience. - 8+ years of overall professional experience in the technology industry in software engineering, developer relations, technical partnerships, including 5+ years of direct hands-on experience in AI and Agentic Security - Proven experience leading, partnering, and scaling developer programs at major technology companies, preferably Security Companies. - Significant technical proficiency in high-performance computing, cloud, AI/ML, and/or security frameworks and libraries. - Excellent interpersonal skills with the ability to distill complex technical concepts for diverse technical and non-technical audiences from engineers to executives. - Experience leading technical collaborations with engineering and product teams - including architectural design, code reviews, technical mentorship, and delivery of technical talks or workshops Ways to Stand Out from the Crowd: - Hands-on experience building or optimizing vertical-specific solutions (e.g., network stacks, bidding algorithms, data pipelines, etc.). - Familiarity with advanced computing, AI, and/or GPU acceleration platforms (insert relevant stack/libraries for the vertical, e.g., CUDA, Triton, NeMo, DOCA). - Successful history of building and scaling developer communities and delivering impactful technical enablement programs. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.

At NVIDIA, we push the boundaries of Artificial Intelligence using Deep Learning every day, designing better algorithms, hardware and software. By joining the Compute Deep Learning Architecture team you would be in an outstanding position to influence all three and help us push the boundaries even farther in large number of fields like datacenters and autonomous machines. We are looking for remarkable candidate passionate about AI and Deep Learning as much as we are. Would you like to make a difference? What you'll be doing: - As a member of our Hardware architecture deep learning team, you will contribute to features that help next-generation GPUs and systems advance the state of AI. - This position requires you to collaborate with other hardware and software engineers as well as DL researchers. - Your day to day work will include analyzing the behavior of various deep learning methods on current and future hardware architectures and propose new features to accelerate it. The features could be HW, SW or Algorithmic - usually combining all. - The main focus of this job is from hardware architecture perspective and workload performance. What we need to see: - A degree or equivalent experience in computer science, electrical engineering or related field. - 8+ years of experienc e in at least some of the following relevant areas is required: Performance, Hardware Architecture, Deep Learning analysis. - A familiarity with GPU computing (Nvidia or others) is a plus. - Excellent interpersonal skills, people who like to collaborate and work within a team. - innovation, motivation and passion. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. An AI-powered robot can communicate and learn motor skills through trial and error. This is truly an outstanding time. The era of AI has begun. Come and join us!

We are seeking highly skilled and motivated software engineers to join us and build AI inference systems that serve large-scale models with extreme efficiency. You’ll architect and implement high-performance inference stacks, optimize GPU kernels and compilers, drive industry benchmarks, and scale workloads across multi-GPU, multi-node, and multi-cloud environments. You’ll collaborate across inference, compiler, scheduling, and performance teams to push the frontier of accelerated computing for AI. What you’ll be doing: - Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding, data/tensor/expert/pipeline-parallelism, prefill-decode disaggregation. - Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization. - Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite. - Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds. - Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products. What we need to see: - Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing. - Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories. - Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang). - Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute). - Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups. - Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting. Ways to stand out from the crowd - Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang). - Hands-on work with ML compilers and DSLs (e.g., Triton, TorchDynamo/Inductor, MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores). - Experience contributing to containerization/virtualization technologies such as containerd/CRI-O/CRIU. - Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability. - Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts. At NVIDIA, we believe artificial intelligence (AI) will fundamentally transform how people live and work. Our mission is to advance AI research and development to create groundbreaking technologies that enable anyone to harness the power of AI and benefit from its potential. Our team consists of experts in AI, systems and performance optimization. Our leadership includes world-renowned experts in AI systems who have received multiple academic and industry research awards. If you’re excited to build systems, kernels, and tools that make large-scale AI faster, more efficient, and easier to deploy, we’d love to hear from you. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking a Principal Engineer to drive the performance of large-scale AI training and post-training workloads across NVIDIA’s full hardware and software stack. This role sits at the intersection of distributed training, GPU architecture, systems software, deep learning frameworks, and performance engineering. You will analyze and optimize frontier-scale LLM workloads running on thousands of GPUs, drive improvements across frameworks such as PyTorch, JAX, NeMo, and NeMo RL, and use insights from real workloads to help shape future NVIDIA GPU, system, and software roadmaps. We are looking for a deeply technical leader who can operate across abstraction layers: from application-level training behavior to framework/runtime internals, CUDA libraries, communication collectives, memory systems, networking, and GPU architecture. At this level, success means both directly improving performance directly as well as setting technical direction, raising the bar for the organization, and influencing multi-functional decisions across NVIDIA. What you will be doing: - Lead end-to-end performance analysis and optimization of innovative LLM pre-training and post-training workloads on the latest NVIDIA hardware and software platforms. - Drive workloads closer to speed-of-light performance by identifying and removing bottlenecks across compute, memory, communication, scheduling, parallelism strategy, kernel efficiency, framework overhead, and system-level scaling. - Develop production-quality software, tools, models, benchmarks, and analysis infrastructure that improve training performance, efficiency, and developer velocity across NVIDIA’s AI software stack. - Build and refine performance models, workload characterizations, and simulation methodologies to guide future GPU, networking, system, and software architecture decisions. - Serve as a technical authority for AI training performance, partnering closely with teams across GPU architecture, systems, CUDA libraries, compilers, networking, frameworks, product management, and applied AI. - Translate workload insights into concrete hardware and software recommendations, and advocate for changes that improve performance and efficiency across the AI ecosystem. - Mentor and provide technical leadership to engineers across the organization, helping establish best practices for large-scale AI performance analysis and optimization. What we need to see: - A MS, or PhD (or equivalent experience) in Computer Science, Electrical Engineering, Computer Engineering, or a related field, with 12+ years of relevant work or research experience. - Demonstrated principal-level technical impact in one or more of the following areas: large-scale AI training systems, GPU performance optimization, distributed systems, high-performance computing, ML frameworks, compilers/runtimes, or hardware/software co-design. - Deep hands-on experience analyzing and optimizing performance of large-scale deep learning workloads, especially transformer-based models, LLM pre-training, reinforcement learning, fine-tuning, or other post-training workloads. - Strong understanding of GPU and AI accelerator architecture from individual accelerators to datacenter-scale systems. - Experience with distributed training techniques such as data parallelism, tensor parallelism, pipeline parallelism, expert parallelism, sequence parallelism, activation checkpointing, mixed precision training, and communication/computation overlap. - A strong track record of using profiling, tracing, benchmarking, and performance modeling tools to diagnose complex bottlenecks and drive measurable improvements. - Excellent communication and technical leadership skills, with the ability to influence architecture and software decisions across multiple teams without relying on direct authority. GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud. We craft computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots. AI has the potential to spur a wave of social progress unmatched since the industrial revolution. This opportunity offers you the ability to collaborate with some of the most forward-thinking and hard-working people in the world, shaping the future of AI in a creative and autonomous work environment that encourages innovation. If you're passionate about working across the full hardware & software stack—from GPU architecture to application code—to achieve optimal performance, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. What you’ll be doing: - Designing, implementing, and delivering innovations for managing GPU based AI servers with focus on OOB management, firmware development, server architecture and building systems for enterprise. - Working with a global team of BMC developers on NVIDIA server designs. - Designing and developing performance optimized active monitoring BMC solutions using DMTF Standards including MCTP, Redfish, SPDM and PLDM specifications. - Instrumenting code to ensure maximum code coverage, writing and automating unit tests for each implemented module and maintain detailed unit test case reports. - Providing software quality reports based on static analysis, code coverage, CPU load. - Partner with security team to ensure developed code is in line with product security goals. - Working closely with hardware teams to influence hardware design and review HW architecture & schematics. - Working with QA/Test architects to come up with proper test tools and automation for qualifying the whole system software and firmware stack. What we need to see: - Bachelor’s Degree or higher in Electrical Engineering or Computer Science, and 5+ years of experience, with demonstrated strong ability as individual contributor. - Domain expertise in BMC Firmware development on X86 or ARM Platforms including BMC-BIOS communication, thermal management, power management, firmware update, device monitoring, firmware security, etc. - Strong experience with AMI/Insyde or OpenBMC Firmware architecture. - Be able to lead BMC firmware development through the whole project developing phases and success to mass production. - Solid experience of end-to-end delivery of high-end enterprise servers from definition to customer deployment. - Solid understanding of low-level interfaces between SBIOS, BMC and OS like I2C/SPI/PCIe/JTAG etc. PCIe enumeration, IO at platform level for enterprise systems. - Experience working closely with HW teams, ODMs and vendors to introduce and support server platforms. - Experience with C/C++ development, bash/python for scripting, and debugging skills in embedded Linux operating environments. - You should possess excellent written and oral communication skills, good work ethics, high sense of team-work, love to produce quality work and commitment to finish your tasks every single day. You are a self-starter who loves to find creative solutions to exciting problems. Ways to stand out from the crowd: - Contributor to industry standards like Open Compute, IPMI, DMTF Standards, and open source. - Proven record in delivering BMC or equivalent manageability stack for enterprise servers with AMI SPX  firmware stack. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We are seeking an ambitious Senior Solutions Architect - AI Factory Deployment to join our NVIDIA Infrastructure Specialists team in Santa Clara! This role is uniquely positioned to develop, deploy, and validate AI factories end to end. You will focus on running and debugging AI/LLM workloads and benchmarks on Linux-based GPU clusters, using NCCL and collectives like AllReduce and AllToAll to improve performance and scalability. As part of our world-class team, you will bring to bear observability and automation to improve benchmarks and validation. You will serve as the expert when workloads or benchmarks do not perform flawlessly. You will collaborate across NVIDIA to ensure AI factories are prepared for customers, validating hardware and software for modern AI deployments. What You Will be Doing: - Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters. - Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks. - Own the execution of key AI/LLM benchmarks, including setup, orchestration, result collection, and analysis. - Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform. - Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health. - Develop automation (Python, Shell) for running benchmarks, collecting results, and performing regression checks - Examine communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll. - Recommend changes to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency. - Work closely with hardware, software, networking, datacenter, and product teams to prepare AI factories for customer use. - Contribute to documentation, guidelines, and readiness collateral that support internal collaborators and customer-facing teams. What We Need to See: - Bachelor’s degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field. - More than 6+ years of experience managing Linux-based systems in HPC, distributed systems, or extensive AI/ML settings. - Hands-on experience running AI/ML workloads on multi-GPU and/or multi-node clusters, with practical knowledge of NCCL. - Solid grasp of collective communication patterns, particularly AllReduce and AllToAll, and how they are applied in contemporary ML/LLM training. - Familiarity with LLM training and/or inference workflows using frameworks such as PyTorch or TensorFlow. - Proficiency with Python and Shell/Bash for scripting, automation, and tooling. - Experience with benchmarking (crafting, executing, and interpreting performance benchmarks). - Comfortable working with observability data (metrics, logs, dashboards) to troubleshoot and optimize complex distributed workloads. - Strong communication skills and the ability to work effectively with cross-functional teams. Ways to Stand Out From the Crowd: - Experience with AI factory or large-scale AI infrastructure build, deployment, or operations. - Background in HPC performance engineering, SRE, or systems performance analysis for GPU-accelerated environments. - Familiarity with observability stacks (e.g., metrics/monitoring, logging, tracing systems) used for large distributed systems. - Experience building automation and CI-style pipelines for running and validating benchmarks at scale. - Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a Senior Signal & Power Integrity Engineer! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! This position offers the opportunity to have real impact in a multifaceted, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. What you'll be doing: - Lead board/system SI design activities, PCB stack up design, material selection, design guide implementation, layout review, and post-layout analysis. - System-level signal integrity simulation of PCIE, LPDDR/DDR/GDDR, MIPI, HDMI, USB and other interfaces. - Analyze and optimize Power delivery network (PDN) on PCBs. - Work closely with Package and PCB Design teams crafting solutions for system SI/PI performance. - Work with Application Engineering supporting customer board designs. - TDR & VNA measurement for PKG/PCB material characterization and model correlation What we need to see: - BS/MS in Electrical Engineering (or equivalent experience) with minimum 4 years of experience as a SI/PI engineer - Good understanding of electromagnetics, channel components and transmission line theory - Experience with design and implementation of one or more high speed electrical interfaces, such as PCIE, LPDDR/DDR/GDDR, MIPI, HDMI, USB etc. - Hands on experience with HFSS, Sigrity, Hspice or similar industry standard simulation tools - Experienced with Cadence Allegro PCB designer and Constraints Manager and or other PCB stack up designer tools. - Understanding of impacts of high-volume PCB manufacturing on channel signal integrity Ways to stand out from the crowd: - Expertise in one or more of the high-speed interface SI/PI designs on any industry standard system platforms. - Exposure to package design, interface timing budgets and system modeling - Familiarity with high-speed transmitter, receiver design and various equalization schemes - Familiarity with various signaling schemes like NRZ, PAM4 is a plus. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's AI Software Platforms team is building the next generation of agentic AI infrastructure that lets coding agents synthesize, optimize, and deploy GPU kernels automatically. This job focuses on crafting AI kernels that connect data pipelines, evaluation suites, and GPU-accelerated runtimes. This helps developers safely release faster, better-performing inference and training solutions. As Product Managers at NVIDIA, we enable developers to be successful on the NVIDIA platform and push the boundaries of what is possible with AI deployments. In this role, you will act as the internal champion for AI agents and LLM-based coding workflows that generate optimized kernels. You'll partner closely with engineering, research, and customers to define strategy, develop roadmaps, and build products that span the entire agent lifecycle — from data collection and synthetic data generation to evaluation, deployment, and continuous improvement. What you'll be doing: - We architect agent-focused products that let coding agents generate, refactor, and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures. - Define the end-to-end data lifecycle for agent training and evaluation, including dataset curation, artificial data creation, and benchmark suites for correctness, latency, and adaptability. - Partner with CUDA, kernel, and compiler engineering teams to integrate agents with compilers, profilers, execution sandboxes, and runtimes in a safe, observable way. - We collaborate with internal and external developers, NVIDIA leaders, and ecosystem partners to drive multi-agent orchestration, prioritize features, and deliver launches and messaging for agentic AI kernel generation. What we need to see: - 7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; we care deeply about end-to-end ownership and impact. - Proven experience in the AI agent or LLM space, including developing or productizing coding agents. Experience with multi-agent orchestration and self-healing or code loops that improve over time is required. Candidates should also have worked on connecting agents to compilers or execution environments. - Proven record of crafting and releasing automated testing or evaluation suites. These suites measure agents on non-subjective metrics such as correctness, performance, and latency. We rely on data to guide both development and iteration. - BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems. Ways to stand out from the crowd: - PhD or equivalent experience in Computer Engineering, Computer Science, or another technical specialty. - Track record building or launching coding-agent platforms or copilots used by development teams at scale, and contributions to performance-critical open-source projects (e.g., Triton, TVM, FlashAttention, kernel libraries, agent frameworks) with clear community adoption and impact. - Research experience in GPU kernel optimization, collective or group communication algorithms, multi-agent systems, or ML model serving / inference architectures that shows how you think about systems end-to-end. - Experience crafting cost-per-inference or cost-per-token models that incorporate hardware utilization, energy efficiency, and cluster scaling, and using those models to guide product strategy and tradeoffs. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is an accelerated computing platform company, that includes GPU, DPU, Networking and software for Professional Visualization, Accelerated Computing, Generative AI, ML. Be an integral part of a team responsible for a significant and rapidly growing revenue contribution at NVIDIA. We are looking for a strategic account manager to raise awareness, increase the adoption and accelerate the development and deployment of all NVIDIA's accelerated computing platform with a major CSP. This full-time position requires strong technical background and close working relationships with CSP organizations, NVIDIA Solution Architects, Business Units, and Developer Relations, to drive revenue and partnerships for the company through adoption of NVIDIA's accelerated platforms. What you’ll be doing: - Lead customer engagement and business development activity with a major CSP organizations. - Develop excellent strategic relationships with R&D teams to understand customers' software and accelerated computing needs with a focus on Visualization and Generative AI, DL/ML workloads. - Partner and collaborate with technical teams on GPU application acceleration. - Be the link between the product team and the customer (roadmap updates, tech communications…) What we need to see: - BSEE or equivalent experience (MSEE Preferred) and 12+ years of technical sales, business development or product Management - A proven understanding of the business issues of large CSP, accelerated Computing/ Data Center technology/ Deep learning & machine learning. - Experience selling accelerated solutions to senior executives at named accounts. A real passion for getting things done in a complex sales and technology environment. - Demonstrated track record leading significant revenue and overachieving targets to meet stretch goals. - Ability to provide thought leadership, think strategically and effectively communicate vision (both written and verbal) and influence cross-functionally. Excellent communication skills. Ways to stand out from the crowd: - Strong Background in modern Data Center technology, Professiona Visualization technology and Deep learning/Machine learning. Experience engaging with large hyperscalers. - Successful management of technical products throughout their lifecycle. Track record of successfully growing revenue for new innovative technology-based solutions. Proven ability to build and lead in a matrix-managed team culture. - Excellent communication skills and ability to persuade -- using simple communications that convey sophisticated concepts in a compelling, concise, and creative way. Strong executive presence, polish, and political savvy. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your cash compensation will be determined based on your location, experience and the pay of employees in similar positions with 85% paid through base salary and 15% variable compensation. The cash compensation range is 224,000 USD - 356,500 USD for Level 5, and 248,000 USD - 396,750 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for experienced Systems SW Compiler Engineers for an exciting role in our PTX (Parallel Thread Execution) Compiler Development team. Join the PTX Compiler team and help drive PTX language design and PTX compiler evolution. PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX provides a stable programming model and portable instruction set Architecture (ISA) for NVIDIA GPUs and used by all Compute programming languages compiled to NVIDIA GPUs. PTX is also used as a compiler target by various non-NVIDIA compilers. Work with NVIDIA GPU Architecture and CUDA Programming model teams to build abstractions to expose new GPU features in portable and performant ways in PTX ISA. PTX Compiler (PTXAS) apart from implementing PTX ISA is responsible for PTX Compiler Front End, interaction with optimizer and runtime aspects involving object files, debug information, linkers, loaders and Driver Compiler Interface. As a senior member of the team, you will be responsible for leading efforts to enhance PTX Compiler infrastructure to enhance it to support new compilation models for DL and Generative AI codes. You will be contributing towards evolving programming model for Generative AI and DL applications on GPUs. What you will be doing: - Provide stewardship for PTX ISA and PTX Compiler infrastructure for Generative AI and DL. - Collaborating with architecture and programming model teams to design and implement programming models for next generation GPUs. - Working closely with others to help design compilation stack and strategies for AI and DL workloads. - Collaborate closely with teams developing other related components to ensure compatibility, robustness and high-quality code generation. What we need to see: - BS (or equivalent experience), MS or Ph.D. in Computer Science, Computer Engineering, or related fields. - 6+ years of experience in the area of compiler front end, programming language designs, Compilers/Linkers. - Superb analytical and C/C++ programming skills. - Able to expertly use AI tools and maintain AI generated artifacts - Experience in any one area of compiler development including feature support, code generation and compiler infrastructure. - Excellent and strong interactive, verbal and written communications skills. - Understanding of any Processor ISA (GPU ISA a plus). - Good track record of developing, driving and delivering software products. Ways to stand out from the crowd: - Experience in Programming Languages design and drafting programming language standards. - Knowledge of GPU development and compute APIs such as CUDA, and OpenCL. - Development experience in LLVM IR, MLIR With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Deep Learning, Artificial Intelligence, Autonomous Vehicles, Virtual Reality, etc. Our diverse team of talented, capable, and professional people are our greatest asset! If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a Solutions Architect with experience in GenAI (LLM) model building. This is a highly technical role that requires deep expertise in generative AI, large language models (LLMs), and scalable software engineering practices. We need a passionate, hard-working, expert and creative individual to help us pursue the many opportunities in this region. A Solution Architect is the first line of technical expertise between NVIDIA and our customers, as well as our partners. Your duties will vary from solutions design, training/workshops, troubleshooting, project coordination, industry and marketing speaking engagements, customer relationship management and more. You will primarily support Singapore, but will need to support the wider South East Asia region if required. What you'll be doing: - Be an expert and help customers to customize GenAI (LLM) models and optimise the training performance at scale. - Lead workshops and trainings on NVIDIA's technologies. - Closely partner with other Solutions Architects, engineering, product and business teams at NVIDIA to build GenAI full stack solutions for industry vertical and enterprise use cases. - Work with business managers to thoughtfully craft the vision, actionable and effective strategies for the group. - Encourage industry leaders by articulating the business value from the state of the art in Generative AI. What we need to see: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - 8+ overall years of work-related experience in deep learning, data science or software development with knowledge of parallel computing with GPUs. Specifically focusing on generative AI at scale, with emphasis on training Large Language Models (LLMs) at scale. - Clear written and oral communication skills with the ability to collaborate with management and engineering. Share knowledge with clients, partners and co-workers. - Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences. - Professional or native language proficiency in English and Mandarin. - Ability to travel up to 30% of the time to support customer in South East Asia and beyond. Ways to stand out from the crowd: - Hands-on experience with NVIDIA's NeMo SDKs or Megatron. - Demonstrable ability to customize LLM models with new capabilities as well as for training speed, memory efficiency, and resource utilization. - Familiarity with containerization technologies (e.g., Docker or enroot/pyxis, etc.) and orchestration tools (e.g., Slurm or Kubernetes, etc.) for scalable and efficient model building. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

At NVIDIA, we build groundbreaking products for the following sectors: Deep Learning, High Performance Computing, Gaming, VR, and Automotive. See your efforts in action as developers use your tools to debug, profile and analyze the performance of their systems/applications using the low-level library that you helped to craft as a member of the GPU Foundations Developer Tools team! Innovate as you develop the performance analysis capabilities of NVIDIA hardware along with the Nsight tools and the foundation library to support next generation accelerated computing at datacenter scale. As a system software engineer in the Developer Tools group, you will be developing software that empowers GPU application developers to build outstanding applications that are recognized world-wide. We are seeking a motivated Software Engineer to join our team and contribute to the performance triage development and co-design of our software libraries in collaboration with our Hardware Architecture team. Join our team and gain exciting opportunities to work hands-on at every layer of NVIDIA's outstanding technology. What you will be doing: - Partner with multi-disciplinary teams to design, implement, and verify performance metrics for NVIDIA GPUs - Work on developing and improving methodologies for profiling data collection from GPUs - Define, invent, and improve our GPU profiling library with new features to allow NVIDIA's customers to extract the best performance out of their applications - Read and understand HW specs to design solutions based on it - Craft software unit level tests and framework ensuring the quality of the product - Work on supporting a variety of platforms ranging from super-computers to embedded systems What we need to see: - B.Tech. EE/CS or equivalent with 4+ years of experience, or M.Tech. with 2+ years of experience, or Ph.D. - Strong programming ability in C, C++, Python with proficiency in Data Structures and Algorithms - Solid understanding of Computer Architecture (e.g. x86, ARM CPUs, GPUs) and Operating System concepts - Knowledge of SW design principles, as that's a key as we scale! Ways to stand out from the crowd: - Experience in Device Drivers or System Software development - Knowledge of GPU APIs such as CUDA, OpenCL, OpenGL, Direct3D, Vulkan - Prior experience authoring developer tools, particularly for GPUs - Experience in performance analysis of GPU applications - Ability to read and write in Assembly language, especially for multi-processor architectures NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most dedicated and hard-working people in the world working with us. If the work described above excites you and you are up to the challenge, we want to hear from you. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people in multiple disciplines to help us accelerate the next wave of computing. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, disability status or any other characteristic protected by law.

We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication libraries like NCCL & NVSHMEM for Deep Learning and HPC. DL and HPC applications have a huge compute demand already and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! We are looking for a dynamic and technical leader for our China NCCL team. This is an outstanding opportunity to push the limits on the state-of-the-art and deliver platforms the world has never seen before. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: - Lead, mentor, and grow our China engineering team. Own the end-to-end execution spanning planning, prioritization, quality control and performance. - Interact with customers and researchers to understand their use cases and requirements. Collaborate with engineering, program and product management, and partners to define the product roadmap. - Contribute to feature design and implementation. - Continuously review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are accomplishing work in the most efficient and transparent manner. What we need to see: - 10+ overall years of experience in the software industry with 4+ years of management experience. - Bachelors, Masters, or Ph.D. in CS, CE, EE (related technical field) or equivalent experience. - Specialization in systems software, communication runtimes, or high performance networking. Proven success in managing several complex initiatives or products through the full product life cycle. - Strong understanding of computer systems architecture, networking technologies (RDMA, RoCE, Ethernet, EFA, InfiniBand) and topologies, operating systems principles (aka systems software fundamentals), HW-SW interactions and performance analysis/optimizations. - Hands-on C/C++ programming and debugging skills in Linux. - Experience balancing multiple projects with competing priorities. Flexibility to work and communicate effectively across different teams and timezones. Ways to stand out from the crowd: - Active user or developer of NCCL! - Customer engagement experience in this space. - Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, NIXL, OpenSHMEM, UCX, UCC). - Experience with programming using CUDA, MPI, OpenMP, OpenACC, pthreads. - Knowledge of HPC and ML/DL fundamentals. Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, vLLM, SGLang, TRT-LLM, etc.

We are now looking for a Solution Architect - Deep Learning based in Israel. The individual will collaborate with brand-new Agentic and Physical AI tools alongside Machine learning, Deep Learning, and Data analytics to improve workflows and develop groundbreaking solutions. What You'll Be Doing: - Assisting field business development in guiding the customer through the sales process for GPU Computing products, owning the technical relationship and assisting the customer in building innovative solutions based on NVIDIA technology. - Be a motivating leader in integrating NVIDIA technology into HPC architectures to support scientific and engineering applications. - Be an internal champion for Deep Learning and Data Science among the NVIDIA technical community. - Develop demo solutions and showcase to the AI ecosystem. What We Need To See: - B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience - 5+ years of experience in software development or extensive data analytics, CUDA experience highly desirable. - Experience working with modern Deep Learning software architecture and frameworks including PyTorch, VLLM, Triton - Proven Exposure to GPU technology and CUDA programming - Demonstrable experience in strategy, research, communications. - Capable of working in a constantly evolving environment without losing focus. - Committed with strong analytical and problem solving skills. - Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects. - Direct experience participating in communities (expertly or as highly engaged developer). Ways To Stand Out From The Crowd: - Technical knowledge of developer digital platforms and their trends. - Experienced working with containers, Kubernetes and MLoPS tools - Exposure to C, C++ and Python. - Research background. - Good presentation skills NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most dedicated individuals in the world working for us. If you're creative and autonomous, we want to hear from you! deeplearning

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to take on, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. We would love to hear from you! We are looking for a Senior Mask Layout Design Engineer, someone who is excited to join a growing and dynamic group of diverse individuals responsible for contributing to our latest generation chiplet interface projects What you'll be doing: - Performing physical layout for mixed-signal functions like top level, high speed datapaths and high-speed clocking designs in state-of-the-art sub-micron CMOS technologies using Cadence tools. - You'll work closely with mixed-signal design engineers to customize designs for integration in VLSI products. - Take part in floor planning, custom layout and verifying against design rules and schematics. What we need to see: - Have a BSEE or equivalent experience. - Minimum of 8+ years industry experience in Mask and Layout Design. - Working independently on creating layout with excellent quality - Deep understanding and previous experience for FinFET technology is a must - You are an authority with Cadence custom circuit design tools - particularly virtuoso. - Able to handle fast-paced project and iterate quickly based on designer’s feedback - You can work effectively in a team, good interpersonal skills, enthusiasm, and positive energy. - Scripting languages like perl, python, skill etc.is a plus - Should have knowledge of DRC and LVS checking flows, ability to customize decks. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD for Level 4, and 148,000 USD - 235,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking a highly influential Generative AI Technical Engagement Lead to evangelize for, drive, and support the seamless adoption and accelerate the performance of NVIDIA's accelerated computing stack across critical AI model development initiatives with leading AI model builders. As a key technical driver, you will facilitate deep technical integration and deepen our collaboration around NVIDIA's pioneering hardware, systems, and software libraries within their core development pipelines. This role demands a leader who can operate strategically at the intersection of product vision, advanced technical execution, and high-level customer engagement, directly influencing model architecture optimization, training infrastructure investments, and ensuring the deployment of robust, scalable generative AI solutions that redefine the state-of-the-art. What You Will Be Doing: - Lead Technical Engagement: Engage with senior technical leaders and research teams at AI model builders. Optimize their workflows by leveraging NVIDIA's complete stack for their end-to-end generative AI workflows. Serve as a primary technical point of contact. - Drive Integration: Accelerate the technical integration of NVIDIA's core generative AI technologies. This includes NVIDIA GPU architectures, DGX systems, high-performance networking (InfiniBand), CUDA-X libraries, NeMo frameworks, and inference libraries like TensorRT. Integrate these into the training and inference pipelines of large model builders. - Strengthen Partnerships: Support and strengthen technical implementation plans with partner AI engineering and researchers. Define clear technical objectives, performance breakthroughs, and timelines. Align these with their long-term model development goals and NVIDIA's AI strategy. - Influence Product Roadmaps: Represent the software needs of large model builders to internal NVIDIA product and engineering teams. Contribute to product roadmap decisions by synthesizing findings from large-scale model training and inference environments. Identify cross-industry patterns and advocate for improvements to NVIDIA's core technologies. - Maintain Strategic Relationships: Conduct regular cadence meetings. Document insights, track progress, and provide consistent internal reporting on the adoption and impact of NVIDIA technologies. - Showcase Best Practices: Share standard methodologies for crafting and optimizing highly scalable generative AI model development pipelines across all stages. Focus on the context of large model development. - Stay Updated: Keep current with the latest NVIDIA hardware, libraries, and system updates. Proactively share relevant insights and optimizations with partner model development teams. What We Need To See: - B.S. degree or equivalent experience. - 7+ years of experience in technical product or engineering roles. Focus areas include AI/ML, high-performance computing, or distributed systems. Emphasis on core technology integration and partner collaborations is key. - Extensive experience working with or developing platforms that facilitate large-scale AI/ML training and inference workloads. This includes distributed systems, data infrastructure, and groundbreaking GPU cluster technologies. - Hands-on knowledge of large model architectures (e.g., Transformers, Diffusion Models). Familiarity with core deep learning frameworks (e.g., PyTorch, JAX), and NVIDIA AI acceleration libraries (e.g., CUDA, cuDNN, NCCL, TensorRT, NeMo). Understand techniques for model customization, distributed training, and inference orchestration. - Strong understanding of compute infrastructure environments. This includes GPU cluster management, high-speed networking, parallel file systems, and deployment across on-premise and cloud infrastructures. Possess specific understanding of how large model builders operate at scale. - Proven ability to communicate and influence senior leadership across engineering and research leaders at partner organizations. Link NVIDIA technology capabilities to crucial AI model development and business value. - Successfully navigated fast-paced environments, taking decisive action to achieve results. Especially valuable in AI research collaborations. - Skilled at connecting with engineers, researchers, executives, and multi-functional teams. Ways to Stand Out From The Crowd: - Hands-on experience with large language models (LLMs), diffusion models, distributed training frameworks, and advanced optimization techniques. Ability to prototype quickly and integrate into model development pipelines. - Influence complex product and research decisions by nurturing positive relationships and understanding model builder needs. - Eager drive, strategic curiosity. Anticipate market trends in AI, shape NVIDIA's roadmap, and champion innovation. Understand the large model builder landscape. - Act as a technical advocate for NVIDIA GPU systems and software stack within assigned large model builder partners. Showcase its technical capabilities and strong value proposition. - Understanding of large-scale system performance optimization, container orchestration (e.g., Kubernetes), and Cloud Native technologies for AI workloads. Join NVIDIA at a crucial time as we pioneer Generative AI growth. We are in the infancy stage of building and scaling our Generative AI business for large model development. This role offers a unique opportunity to join this rapid expansion. NVIDIA's hardware, systems, and software libraries are at the heart of this growth. They empower large model builders to revolutionize their operations with powerful AI capabilities. This is your chance to be a key member of a team that will shape the future of AI model development, working with the world's leading AI research labs and the most innovative technologies. Your contributions will directly impact the trajectory of our Generative AI success, making this an unparalleled opportunity for professional growth and significant impact. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community. What you'll be doing: - Analyzing deep learning networks and developing compiler optimization algorithms. - Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. - Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work. What we need to see: - Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience - 3+ years of relevant work or research experience in performance analysis and compiler optimizations. - Ability to work independently, define project goals and scope, and lead your own development efforts. - Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design. - Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. Ways to stand out from the crowd: - Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience. - Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation. - Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch. - GPU kernel generation with high performance and fast build time. - A track record of success in mentoring junior engineers and interns is a bonus. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearning

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can take on, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. The GPU clocks group is looking for an exceptional ASIC Clocks Verification Engineer. The team is responsible for crafting all aspects of GPU clocking. The team collaborates with the front design team to understand the clocking requirements for the chip. The clocks team interacts with the floor-planning and back-end team to help craft the physical floorplan of the chip. The team explains the programming model to the SW team to come up with an efficient clock programming sequence. The team works with the silicon solution team to triage silicon or programming bugs in the lab. What you'll be doing: - As a Clocks team member, you will be collaborating with other architects, ASIC designers and verification engineers to verify high frequency clock structures. - Be able to engage with multiple teams and design the GPU clock structure to satisfy all the architectural constraints. - Your understanding of general verification principles will be valuable to verify the clocks design. - Together with other team members, we deliver clock information to SOC verification team, timing and DFT teams. You will use Perl to improve the productivity of the above teams. - Collaborate with Software and product group to debug GPU clock silicon bugs in our new products. - Understand and design clocking structures to overcome sub-micron design challenges. - You will also identify improvements in the current design and propose and implement new ways to improve the efficiency in the GPU clocking design. What we need to see: - A Master’s degree in Electrical Engineering (or equivalent experience). - Practical experience with SystemVerilog and Universal Verification Method (UVM). - Experience with Design Verification, Logic Design, and Logic Synthesis. - Strong coding skills in Python, Perl, or other industry-standard scripting languages. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you creative and autonomous? If so, we want to hear from you. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's AI Developer Tools organization is seeking a Senior Research Engineer to join our Research team, where we build the AI coding agents, models, datasets, and evaluations at the heart of NVIDIA's strategy to put AI-powered coding tools in the hands of every CUDA developer. The AI coding space is moving faster than any of us have seen — products rise and fall in months — and we work on it from the epicenter: the company whose hardware most of the AI industry runs on. Our team is small, in-person, and high-velocity. We prototype and ship novel coding agents, fine-tune and evaluate code LLMs, publish benchmarks like ComputeEval, and contribute datasets that feed NVIDIA's Nemotron foundation models. We make NVIDIA's core developer tools — including Nsight Compute and Nsight Systems — first-class citizens for AI agents through MCP servers and Agent Skills. The space shifts every few weeks, and we move with it. In this role, you'll bring applied AI research depth to a team that values shipping as much as experimentation. You won't be filling a narrow gap — you'll pick up significant projects across our portfolio, help set direction on new ones, and partner closely with product teams turning our research into features used by NVIDIA developers and external customers. For experienced AI-for-code practitioners who want to do frontier applied work with the stability and resources of NVIDIA behind them, this is a rare seat. What you'll be doing: - Build and improve novel coding agents that help NVIDIA developers write, optimize, and maintain CUDA code — and that work alongside other AI agents in the developer's workflow - Design and ship evaluations, including extensions of our public ComputeEval benchmark, that measure what really matters in AI-powered CUDA development - Fine-tune and specialize code LLMs, and partner with the Nemotron team on the datasets and evaluations that feed NVIDIA's foundation models - Develop Agent Skills, MCP servers, and other tool-use interfaces that make NVIDIA's developer tools (Nsight Compute, Nsight Systems, and more) first-class for AI agents - Generate, curate, and validate synthetic training and evaluation data for CUDA programming - Deliver "net new knowledge" to frontier LLMs through RAG and skill-based systems that keep models current with NVIDIA's fast-moving software stack - Collaborate with partner product teams to turn research prototypes into shipping features used inside NVIDIA and by external customers What we need to see: - B.S. in Computer Science or related technical field or equivalent experience (M.S. or Ph.D. a plus) - 12+ years of industry experience in applied AI/ML, with meaningful recent work in the AI-for-code space — coding agents, code LLMs, AI developer tools, or adjacent systems - Strong proficiency in Python and sound software engineering practices - Hands-on experience fine-tuning or evaluating LLMs, with appropriate humility about the complexity of training and data work - Fluency with the systems side of LLM-powered agents, including practical concerns like context management, prompt caching, tool-use design, MCP, and Agent Skills - Experience designing or contributing to rigorous evaluations for code generation or agentic systems - Track record of shipping — taking work past the prototype stage and into the hands of real users - Comfortable in a small, collaborative, in-person team with fast direction changes and little process overhead Ways to stand out from the crowd: - Public contributions in the AI-for-code space — open-source agents or tools, widely-used benchmarks, influential papers, or blog posts with demonstrated real-world impact - Experience building coding agents or code LLMs that real users rely on every day - Familiarity with CUDA or other GPU programming, and/or with NVIDIA profiling tools (Nsight Compute, Nsight Systems) and libraries (cuDNN, cuBLAS, Thrust, CUB) - Experience with synthetic data generation and quality validation for code - Track record of zero-to-one product work, or work inside a recently-rebooted org with a strong mandate and customer pull With competitive salaries and benefits, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're an applied AI researcher or engineer who wants to ship AI coding tools from the epicenter of the AI industry, and you thrive in a small, in-person team with a clear mandate, this is the role for you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today! The Advanced Technology Group is looking for a highly motivated Senior Systems Software Engineer to join our group. Do you have a proven software development background in advanced computational methods for semiconductor manufacturing and design? Are you seen as a technical leader and an industry expert in several of the underlying fields, such as massively distributed computing, computational geometry, diffractive optics, and artificial intelligence? If yes, then we’d love to hear from you! The job requires creating strategy, driving industry-leading innovation, and working in lean teams to realize these strategies, from invention to production. This role will be located in Hillsboro, Oregon. What you'll be doing: - Working with some of the best technologists in the world to build industry-leading advanced computational methods for semiconductor manufacturing and design. - Exploiting the potential of the GPU to dramatically accelerate these software solutions. - Ultimately, keeping the cadence of semiconductor innovation alive by accelerating semiconductor yield and time to market. What we need to see: - MS (PhD preferred) in Computer Science or Engineering or equivalent experience. - 5+ years of research/industry experience - A track record of innovation, for example by the invention of computer algorithms. - Experience in developing and delivering complex software solutions for enabling or improving semiconductor fabrication and design. - A track record of scaling up software to a level that efficiently utilizes millions of compute hours, and processes petabytes of data. Ways to stand out from the crowd: - Deep understanding of technology and passionate about what you do. - Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. It’s not just technology though! It is our people, some of the brightest in the world, and our company and diverse culture that make NVIDIA one of the most fun, innovative and dynamic places to work in the world! At the center of NVIDIA's culture are our core values - like innovation, excellence and determination, and one team - that guide us to be the best we can be. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 5, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a technical and hands-on Product Manager to lead our product efforts for local AI on Linux and developers. Client AI is the technology platform on top of NVIDIA's client hardware — GeForce RTX, RTX PRO, DGX Spark, DGX Station, and N1X — that enables AI and agents, content creation, and developer workflows. This Product Manager will define how developers, researchers, and enterprise teams build, run, and deploy AI on NVIDIA client platforms running Linux, with a strong focus on enterprise. Generative AI is moving from the cloud to the workstation and the edge. Developers want to prototype, fine-tune, and run frontier models locally. Enterprises want to deploy agents against their private data on-prem. Inference stacks like vLLM, SGLang, TensorRT-LLM, and PyTorch are becoming the default runtime for these workflows. This Product Manager will help NVIDIA win the Linux side of this shift — making our client platforms the best place to build and run modern AI. What you'll be doing: - Define and lead the enterprise agent use case — understand how enterprises deploy agents on-prem, what they need from the platform, and where NVIDIA should invest. - Collaborate with Product Managers that are working on cloud inference backends (vLLM, SGLang, TensorRT-LLM, and PyTorch) to drive and prioritize requirement for local AI. - Own the product strategy and roadmap for the Linux developer experience on NVIDIA client platforms (DGX Spark, DGX Station, RTX PRO workstations, RTX Spark). - Research the developer and enterprise AI ecosystem: interview customers, build personas and user journeys, and map workflows across training, fine-tuning, inference, and agent deployment. - Work hands-on with the latest models, frameworks, and agent tooling so you can represent the developer's point of view in every decision. - Lead cross-functional teams — engineering, DevRel, marketing, partnerships — to ship features and grow adoption. - Influence NVIDIA's GPU, system, and software roadmaps based on what Linux developers and enterprise AI teams actually need. - Build product positioning, technical demos, and sales and partner enablement material for a developer audience. What we need to see: - 8+ years of product management experience, with meaningful time on AI/ML, developer tools, or infrastructure products. - First-hand experience as a developer or engineer — you have shipped code in production and can debug a CUDA, PyTorch, or Docker issue alongside an engineer, not just manage around it. - Deep familiarity with modern AI workflows: training and fine-tuning, inference serving, agent frameworks, RAG pipelines, and evaluation. - Working knowledge of at least one major inference backend (vLLM, SGLang, TensorRT-LLM, or PyTorch-based serving). - Fluency in Linux as a development and deployment environment. - Strong written communication and the ability to translate technical depth for both engineers and executives. - Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience. Ways to stand out from the crowd: - Prior role as an AI/ML engineer, inference systems engineer, or application developer building with LLM APIs and agent frameworks (LangChain, LlamaIndex, MCP). - Experience with model optimization — quantization, distillation, speculative decoding, KV-cache strategies. - Hands-on with CUDA, Triton, or low-level GPU programming. - Background in enterprise software, on-prem deployments, or private AI. - Open-source contributions to AI/ML, inference, or agent projects. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative! What you’ll be doing: - Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization. - Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems. - Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms. - Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware. - Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points. - Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors. - Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues. What we need to see: - Pursuing or recently completed a MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience. - Possess software engineering background with familiarity in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency. - Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation. - Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations. - Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX. - Understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors. - Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements. - Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams. - Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads. Ways to stand out from the crowd: - Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale. - Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability. - Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar. - Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 105,000 CAD - 155,000 CAD for Level 2, and 135,000 CAD - 185,000 CAD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

This Principal Partner Enablement Product Manager, AI Infrastructure owns adoption and alignment for our ODM partners delivering data center solutions to customers. The person in this seat represents our ODM to the DSX suite ecosystem. They will position the primary DSX composition, help partners build accurately, and keep them aligned with the DSX architecture during delivery. Equally important, the person serves as the structured voice of the ODM for our in-house DSX solution and data center engineering teams. They bring real-world partner feedback to build the foundational DSX Plan of Record. The Principal Partner Enablement Product Manager, AI Infrastructure role focuses on three main missions within the partner ecosystem. First, the role leads positioning and enablement by introducing and promoting the DSX platform to ODM partners. This ensures successful design-in and ongoing adoption of the data center blueprint. Second, it supports partners throughout delivery, keeping them aligned as ODMs complete AI Infrastructure data center programs for their customers. Third, it acts as an important feedback and innovation channel that transforms real-world partner insights into actionable suggestions. These suggestions guide product and engineering teams to improve the foundational product strategy. If you are passionate about driving new technologies to market and thrive in a fast-paced environment then this is the perfect job for you. Does this sound like your dream job? Come show us what you got! What You'll Be Doing: - Deeply understand the central DSX platform and translate it into compelling, accessible positioning for ODM engineering and business teams - Lead DSX onboarding and build-in engagements with ODM partners — architecture reviews, reference build adoption, and blueprint compliance - Maintain continuous ODM alignment following the DSX data center framework throughout the delivery lifecycle, identifying and addressing deviations before they reach the customer - Serve as the primary interface between ODM partners and the internal DSX product team. Aggregate and clearly communicate partner feedback on stack usability, deployment gaps, and real-world constraints. - Bring ODM field findings clearly and credibly into the core POR process of DSX. Advocate for product optimizations that reflect what partners encounter when deploying mid to senior-level roles at scale. - Develop and sustain constructive connections with leadership in ODM engineering, ensuring they regard DSX as an essential investment instead of a mere compliance obligation - Support the development of enablement materials — technical briefs, build guides, deployment playbooks — that make it easier for ODMs to adopt and stay on the DSX blueprint - Track and report ODM adoption depth, alignment with the blueprint, and feedback themes to DSX leadership What we need to see: - 15+ years in product management, technical enablement, or solutions engineering. This includes significant experience working with or inside ODM partners on data center or computing infrastructure programs. - Hands-on experience with AI Infrastructure delivery from the ODM side — understands the design-in process, program pressures, and how architectural decisions get made - Demonstrated ability to enable external partners to adopt a complex technical stack, including design-in programs, architecture reviews, or blueprint compliance - Prior experience as a conduit between external partners and internal product teams — comfortable synthesizing field feedback into actionable product input - Strong grasp of data center architecture and the infrastructure layers that make up a full DC deployment - Technically proficient enough to engage credibly with ODM hardware and systems engineers on DSX architecture, reference builds, and deployment blueprints - Strong product instincts — able to distill qualitative ODM feedback into clear, prioritized input for the core DSX POR - Excellent written and verbal communication; able to position the DSX stack at both executive and engineering levels within ODM organizations - A Bachelor's degree or equivalent experience, or a Master's degree or similar experience in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a related area Ways to stand out from the crowd: - Mandarin proficiency (spoken and written) is a plus — given the depth of daily engagement with original device manufacturers’ engineering and leadership teams - Prior experience working at or embedded with a Tier 1 ODM on a DC infrastructure program - Familiarity with DSX architecture, internal build review processes, and how the DSX is structured. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a Senior DL Algorithms Engineer for LLM/Omni model optimizations! Seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning workloads. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. What you will be doing: - Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack. - Contribute new features, fix bugs and deliver production code to open-source frameworks like TRT-LLM, vLLM, SGLang, FlashInfer, etc. - Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance. - Benchmark state-of-the-art offerings and perform competitive analysis for NVIDIA’s SW/HW stack. - Co-design with partner teams to develop the next generation of AI models and services. What we want to see: - PhD in CS, EE or CSEE or equivalent experience. - 3+ years of experience. - Strong background in deep learning and neural networks, in particular inference. - Experience with performance profiling, analysis and optimization, especially for GPU-based applications. - Proficient in PyTorch or equivalent frameworks for AI, or HPC-heavy application development. - Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Ways to stand out from the crowd: - Proven experience with processor and system-level performance optimization. - Deep understanding of modern LLM/Diffusion architectures. - Strong fundamentals in algorithms. - GPU programming experience (CUDA or OpenCL) is a strong plus. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Are you a Mask Layout Design Engineer? We are looking for a Senior Mask Layout Design Engineer, someone who is excited to join a growing and multifaceted group of diverse individuals responsible for handling meaningful high-speed mixed-signal circuit designs. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to take on, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. We would love to hear from you! What you'll be doing: - Performing physical layout for mixed-signal functions like PLL's, high speed SerDes, Analog to Digital converters, ESD structures designs in innovative sub-micron CMOS technologies using Cadence tools. - You'll work multi-functional with ASIC and mixed-signal engineers to customize designs for integration in VLSI products. - Take part in floor planning, custom layout and verifying against design rules and schematics. What we need to see: - Have a BSEE or equivalent experience and minimum of 8+ years industry experience. - Deep understanding of analog circuit layout concepts in submicron CMOS technologies. - You are an authority with Cadence custom circuit design tools - Experience running and debugging with verification tools such as Dracula, Hercules, Calibre, and Primeyield. - You are able to work optimally in a team, good interpersonal skills, passion and positive energy. - Proficient in scripting languages like perl, python, skill etc. - Should have knowledge of DRC and LVS checking flows, ability to customize decks. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking outstanding Performance Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications. Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field! What you’ll be doing - Design and evaluate hardware architectures to improve performance, efficiency, and scalability of production AI workloads. - Analyze and optimize large-scale deep learning workloads, especially LLM inference/training in real-world deployments. - Build and use performance and power models (Python/C++) to drive architecture and product decisions. - Identify and resolve system bottlenecks across compute, memory, and interconnect. - Evaluate PPA trade-offs and guide feature prioritization for next-generation GPU/ASIC designs. - Partner closely with software, systems, and product teams to align hardware capabilities with workload requirements. What we need to see: - MS or PhD in a relevant field (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience. - 5+ years of hands-on experience in GPU/ASIC architecture, parallel computing, or system performance engineering. - Experience with deep learning workloads in production environments (training and/or inference). - Proficiency in Python and C++ for building performance models, simulators, or analysis tools. - Solid understanding of system architecture: memory hierarchy, data movement, and scalability. - Prior experience debugging, profiling, and performance tuning on real systems. - Ability to work across team and drive decisions in fast-paced product environments. Ways to stand out from the crowd: - Experience translating workload behavior into concrete hardware or system-level improvements. - Practical experience with LLM inference optimization: batching, disaggregation, KV-cache management, latency/throughput tuning. - Familiarity with production inference systems (e.g., scheduling, multi-node scaling, resource utilization) Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative! What you’ll be doing: - Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization. - Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems. - Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms. - Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware. - Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points. - Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors. - Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues. What we need to see: - Pursuing or recently completed a MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience. - Possess software engineering background with familiarity in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency. - Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation. - Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations. - Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX. - Understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors. - Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements. - Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams. - Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads. Ways to stand out from the crowd: - Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale. - Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability. - Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar. - Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice and join us today! This is a dynamic team working with pioneering, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! We are looking for a senior engineer to be part of the mixed-signal design team building next generation NVLINK. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. What you'll be doing: - Develop and implement high speed electrical/optical interfaces and analog circuits. You will have hands on experience taking innovative integrated circuit designs at data rates of 25Gbps and higher from concept through silicon characterization. - Help by defining circuit requirements and complete design from schematic, layout, and verification to characterization. - Conduct schematic design of deep-submicron CMOS technologies using Spectre, Hspice or like. - Lead architecture, transistor design and verification using industry standard EDA tools such as Cadence virtuoso. - Optimize circuit to meet the specifications for system performance. - Work closely with layout engineers by providing detailed floorplan and guidance for matching and high-speed routings. - Provide support for post-silicon bring-up and debugging. What we need to see: - Master of Science or Ph.D. in Electrical Engineering, Computer Engineering or related field with strong analog design background (or equivalent experience) - 6+ years analog design experience - CMOS Analog / Mixed Signal Circuit Design Experience in deep sub-micron process (especially in FINFET) - Experience with design and verification tools (Cadence's IC design environment, analog circuit simulation tools like Spectre, HSpice, Finesim, XA) - Experience in crafting test bench environments for component and top level circuit verification - Behavioral modeling of analog and digital circuits - Strong debugging and analytical skills - Analog simulation for noise analysis, loop stability analysis, ac/dc/tran analysis, monte-carlo, etc. - Strong interpersonal skills and ability & desire to work as a phenomenal teammate are huge plus. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is building the world’s leading AI company, and we are looking for an expert AV and GenAI Solutions Architect to help assist customers with adoption of NVIDIA's full-stack technologies as well as building and deploying solutions around Generative AI and Physical AI and other related GPU-accelerated technologies in which intelligent agents can learn, reason, and interact the world. As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of autonomous vehicles, in-vehicle AI assistance, and ride sharing algorithms among other things. A Solutions Architect is the first line of technical expertise between NVIDIA and customers so you will engage directly with developers, researchers, and visionary scientists at some of the most strategic customers as well as work directly with business and engineering teams on product strategy as it pertains to these customers. Join us in this exciting endeavor! What you'll be doing: - Engage with customers to help them scope and develop solutions for building AV perception and planning models and pipelines, simulations, synthetic data generation, and software in the loop testing, AI enhanced manipulation and navigation workflows using NVIDIA's Physical AI platforms and CUDA-X libraries. - Provide hands-on technical mentorship to partners and customers on Nvidia GenAI stack. Guide customers to develope and deploy Agentic AI workflows on our platforms, quantifying the benefits of our accelerated computing software and hardware. - Partner with Sales, Engineering, Product and other Solution Architect teams to drive NVIDIA full stack adoption. Develop a deep understanding of customer workflows and requirements, lead proof-of-concepts evaluations and provide internal feedback to drive continuous product improvements. - Build collateral (notebooks, github repos, demos, etc.) applied to workflows such as AV and GenAI data curation, model training and validations, LLMs, VFMs, video encoding/decoding, etc. What we need to see: - Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience. - 8+ years of hands-on experience in a technical AI role, with a strong emphasis on AV End-to-End models and GenAI model development. - Experience writing production codes in Python, or C++ and proficiency with Linux. - Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes. - Strong understanding of AV systems (Sensors, dynamics, perception, prediction, planning, control). - Experience with DL and RL algorithms and frameworks such as PyTorch. - Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams). - Effective verbal/written communication, and technical presentation skills. - Self-starter with a vision for growth, real passion for continuous learning and sharing findings across the team. Ways to stand out from the crowd: - Experience with AV sensors, data curation pipelines, world models, simulations workflows and tools e.g., Carla. - Experience with Agentic AI frameworks, tools, and protocols like LangChain, LangGraph, MCP or equivalent experience. - Understand computational characteristics of Multimodal LLMs, VLMs, DiT, etc. - Experience in deploying LLM models at scale on mainstream cloud providers (e.g., AWS, Azure, GCP). - Proven track record to profile and optimize inference latency and throughput, memory and I/O utilization. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work , to amplify human creativity and intelligence. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world! Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification, and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: - As an integral member in our team, you will work on exploring Applied AI solutions for DFX and VLSI problem statements. - Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows. - Work on deploying predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips. - Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions. - Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies. - Work closely with DFX teams to integrate Agentic AI workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies. - Define how data will be collected, stored, consumed and managed for next-generation AI use cases. - You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: - BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning - Experience in Applied ML solutions for chip design problems - Significant experience in deploying generative AI solutions for engineering use cases - Good understanding of fundamental DFT & VLSI concepts - ATPG, scan, RTL & clocks design, STA, place-n-route and power - Experience in application of AI for EDA-related problem-solving is a plus - Excellent knowledge in using statistical tools for data analysis & insights - Strong programming and scripting skills in Perl, Python, C++ or TCL desired - Strong organization and time management skills to work in a fast-pace multi-task environment - Self-motivated, independent, ability to work independently with minimal day-to-day direction - Outstanding written and oral communication skills with the curiosity to work on rare challenges NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you! LI-Hybrid

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you'll be doing: As a Solutions Architect in NVIDIA AI Technology Center (NVAITC), you will be leading the way in AI research and application. You will: - Serve as a research & engineering subject matter expert (SME), driving internal and external collaborations with academia and industry. - Serve as the technical expert for NVIDIA technologies, in particular ALCHEMI and more broadly, our CUDA-X libraries. - Keep up to date on the latest AI advances in Chemistry and Materials Science, including atomistic simulation, machine learning interatomic potentials (MLIPs), quantum chemistry, and generative models for molecules and materials - Lead and mentor junior technical members, encouraging a collaborative and inclusive environment. - Collaborate with the management team to develop and implement strategic engagements and projects involving institutes of higher learning (IHLs), industry, and government, ensuring seamless delivery and implementation. - Play a key role in NVIDIA’s global initiative to foster accelerated AI throughout the ecosystem by facilitating and supporting workshops, symposiums, and technical sharing sessions. - Mentor collaborators, interns, and students, providing mentorship and skills training to successfully implement AI projects. - Develop NVIDIA technology-related tutorials, demos, and workshop materials, showcasing our world-class innovations. What We Need To See: - Demonstrated 5+ years of experience ‘AI for Chemistry and Materials Science’ and familiarity with NVIDIA technologies (e.g., ALCHEMI, cuEquivariance, cuEST). - A PhD or equivalent experience in Computational Chemistry, Materials Science and Engineering, Computer Science, or related research domains. - A proven history of guiding and assisting research & engineering projects. - Technical mentoring experience in areas such as research/engineering projects. - Experience in AI ecosystem development and collaboration initiatives. - Proficiency in coding with Python and using AI/ML libraries such as PyTorch. - Excellent time management skills, self-motivation, and the ability to work both independently and within a team. - Effective communication skills, enabling you to articulate complex concepts clearly and concisely. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time. Do you want to help drive the performance of next-generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high-performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team. You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you're passionate about performance, systems, and building infrastructure that drives real-world impact, we want to hear from you. What You’ll Be Doing: - Design and develop performance testing frameworks for deep learning compilers and workloads - Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes - Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads - Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities - Partner with compiler and architecture teams to debug and resolve performance issues - Develop tools and dashboards for performance visualization, reporting, and insights - Enable scalable testing across diverse GPU systems and environments - Improve infrastructure to ensure reliable, reproducible, and high-signal performance data What We Need to See: - BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field - 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization - Strong programming skills in Python (C++ is a plus) - Experience with CI/CD systems and automation frameworks - Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems) - Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT - Background in data analysis, profiling, and regression tracking - Ability to debug complex system-level issues across software and hardware layers Ways to Stand Out from the Crowd:: - Experience with GPU performance analysis and optimization - Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow) - Experience building performance dashboards and large-scale telemetry systems - Familiarity with hardware/software co-design or low-level performance tuning - Experience with distributed testing infrastructure or large-scale benchmarking systems With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearning

NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Singapore team. We are dedicated to the development and optimization of GPU-accelerated efficient AI computing, covering language model, visual generation, and robotics. We focuses on pushing the boundaries of generative AI by designing models that are not only powerful but also efficient in terms of computational resources. You will be part of an amazing collaborative research team that consistently publishes at the top venues in machine learning, robotics and computer vision. Your contributions have the chance to create real impact on our products. What you'll be doing: - Research, design and accelerate novel generative AI models - Publish original research - Collaborate with other team members and teams - Mentor interns - Speak at conferences and events - Transfer technology to product groups - Collaborate with external researchers What we need to see: - Excellent knowledge of LLM and foundation models - Publication at leading conferences (ie. CVPR, ICML, ICLR, ICCV, NeurIPS, etc) - 2 years of experience. Bachelor, master, or PhD degree in computer science or electrical engineering with strong research track records. - Excellent programming skills in some rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA) is a plus - Knowledge of common machine learning frameworks, such as PyTorch - Excellent communication skills NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. Looking forward to hear from you.

NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Singapore team. We are dedicated to the development and optimization of GPU-accelerated efficient AI computing, covering language model, visual generation, and robotics. We focuses on pushing the boundaries of generative AI by designing models that are not only powerful but also efficient in terms of computational resources. You will be part of an amazing collaborative research team that consistently publishes at the top venues in machine learning, robotics and computer vision. Your contributions have the chance to create real impact on our products. What you'll be doing: - Research, design and accelerate novel generative AI models on NVIDIA GPUs - Publish original research - Collaborate with other team members and teams - Mentor interns - Speak at conferences and events - Transfer technology to product groups - Collaborate with external researchers outside NVIDIA What we need to see: - Excellent knowledge of LLM and foundation models - Publication at leading conferences (ie. CVPR, ICML, ICLR, ICCV, NeurIPS, MLSys, etc) - 4 years of experience. - PhD degree in computer science or electrical engineering with strong research track records. - Excellent programming skills in some rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA) is a plus - Knowledge of common machine learning frameworks, such as PyTorch - Excellent communication skills NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. Looking forward to hear from you

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA’s autonomous driving solutions. As a member of our perception team, you will work on building world-class 3D obstacle perception solutions based on multi-sensor fusion, including cameras, ultrasonic sensors, and radar, to estimate high-resolution reconstruction of the world. The primary approach will be deep learning. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime. What you’ll be doing: - Perception experts with application focus will be on multi-sensor fusion based deep learning model development for obstacle perception/fusion in complex driving environments. - Applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios. - Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization. This includes careful data verification, model architecture design, understanding details of loss function engineering, and being capable of finding detailed ML bugs and iterating toward perfection. - Productize the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and SW robustness, with a strong emphasis on production deep learning model development. - Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, so that value of data is maximized. What we need to see: - 10+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch). - Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction. - Proven experience in production deep learning model development, including careful data verification, model architecture design, loss function engineering, and debugging ML models. - Experience in data-driven development and collaboration with data and ground truth teams. - Strong programming skills in python and/or C++. - Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other. - BS/MS/PhD in CS, EE, sciences or related fields (or equivalent experience) Ways to stand out from the crowd: - Experience on end-to-end deep learning model development is a plus. - Proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with multi-sensor input. - Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications. - Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic, and sensor fusion principles. - Experience with development in CUDA language. The ability to implement CUDA kernels as part of training or inference pipelines. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and SW/HW teams running AI workload in GPU cluster. As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the performance and efficiency of the system. What you’ll be doing: - Build internal profiling and analysis tools for AI workloads at large scale - Build debugging tools for common encountered problems like memory or networking - Create benchmarking and simulation technologies for AI system or GPU cluster - Partner with HW architects to propose new features or improve existing features with real world use cases What we need to see: - BS+ in Computer Science or related (or equivalent experience) and 6+ years of software development - Strong software skills in design, coding (C++ and Python), analytical, and debugging - Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference. - Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking - Experience with NVIDIA GPUs, CUDA Programming and NCCL - Motivated self-starter with strong problem-solving skills and customer-facing communication skills - Passion for continuous learning. Ability to work concurrently with multiple global groups Ways to stand out from the crowd: - Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms - Solid experience in large AI job performance analysis for training/inference workload - Knowledge of Linux device drivers and/or compiler implementation - Knowledge of GPU and/or CPU architecture and general computer architecture principles LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for PhD research interns excited to advance the next generation of large language models through reinforcement learning. Our applied deep learning research team at NVIDIA has helped pioneer projects such as Megatron, MT-NLG, and DLSS. We build state-of-the-art foundation models and develop new methods to improve their reasoning, alignment, reliability, and ability to solve real-world tasks. This internship will focus on algorithmic research at the intersection of reinforcement learning and large language models. You will design, implement, and evaluate new RL-based methods for improving LLM behavior, with a strong emphasis on hands-on experimentation and rapid prototyping at scale. What you will be doing: - Develop and prototype reinforcement learning algorithms for large language models - Explore methods for improving reasoning, alignment, instruction following, and multi-turn interaction - Design experiments to evaluate model behavior, robustness, hallucination, and task performance - Implement research ideas in Python and PyTorch, and run experiments on large-scale GPU clusters What we need to see: - Pursuing a PhD in AI, ML, CS, CE, EE, Math, Physics, or a related field - Strong background in reinforcement learning and natural language processing - Excellent programming skills, especially in Python - Experience with deep learning frameworks such as PyTorch - Comfort with experimental research, debugging models, and working with large-scale training pipelines Ways to stand out from the crowd: - Publications or open-source contributions in RL, LLMs, alignment, reasoning, or post-training - Experience with RLHF, RLAIF, policy optimization, reward modeling, or agentic LLM systems - Strong intuition for both algorithms and large-scale implementation If you are excited about using reinforcement learning to make language models more capable, reliable, and useful, this team could be a great fit. Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 30 USD - 94 USD. You will also be eligible for Intern   benefits . Applications for this job will be accepted at least until May 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a Senior Mixed-Signal/Analog/IO Circuit Design Engineer – someone who is excited to join a growing group of diverse individuals responsible for handling challenge high-speed memory interface designs. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. What you'll be doing: - Mixed-Signal/Analog circuit design for High Speed Memory I/O Interfaces - Solve challenge of circuit designs in deep submicron CMOS FinFET processes - Take designs through productization and be involved in all stages of development - Work with multi-functional teams to optimize the designs What we need to see: - Advanced High-Speed Design Expertise:  5+ years of proven experience in high-speed memory (LPDDR, DDR, GDDR, HBM) or SerDes design, underpinned by a BSEE or MSEE and a deep understanding of system-level timing budgets and specifications. - FinFET Circuit Mastery:  In-depth technical command of deep submicron CMOS FinFET processes, with the ability to navigate complex circuit design challenges and implementation nuances. - Reliability & Physical Integrity:  Comprehensive knowledge of device reliability, ESD, and Latch-Up requirements, including the ability to supervise layout development to ensure strict adherence to these critical rules. - Full-Flow Tool Proficiency:  Expert-level command of Cadence custom design environments and industry-standard simulators (Hspice, XA, FineSim, Spectre), with a working knowledge of Verilog, Nanotime, or Matlab. - Silicon-to-System Perspective:  Ability to bridge the gap between die and system, offering insights into package substrate design, board-level constraints, and Power Delivery Network (PDN) analysis. - Collaborative Leadership:  A proactive teammate with strong interpersonal skills, capable of mentoring junior engineers and performing hands-on validation using high-end lab test and measurement equipment. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Development Engineer; you will collaborate with multi-functional groups. SWQA Developer Engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA Engineer can improve productivity or optimize test plan. As a SWQA Developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What you’ll be doing: - Review product requirements and develop test matrix. - Build test plan, design test case, execute and report test progress, bugs, and results to management. - Automate test cases and assist in the architecture, crafting and implementing of test frameworks. - Manage bug lifecycle and co-work with inter-groups to drive for solutions. - In-house repro and verify customer issues/fixes. What we need to see: - BS or higher degree or equivalent experience in CS/EE/CE plus equivalent with 3+ years QA experience. - Proficient in Unix/Linux and shell/python programming skills. - Rich experience in test cases development, tests automation in API/UI and failure analysis. - Solid experience with AI development tools, including creating test cases, automating test cases, and ensuring comprehensive code coverage, among other related tasks - Good knowledge and hands-on experience in model testing and LLM benchmarking - Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc. - Excellent communicator, fluent written and verbal English. - Good teamwork with ability to work independently. - Passion to learn new hardcore technology. Ways to stand out from the crowd: - Experience working with NVIDIA GPU hardware is a strong plus - Background in deep learning frameworks is a plus - Experience in parallel programming ideally CUDA/OpenCL is a plus

Nvidia is looking for a Senior Software Engineer to join our Video/Multimedia Architecture & Algorithms (A&A) team — the people who build tomorrow’s NVENC and NVDEC, the dedicated video encode and decode engines that power streaming, cloud gaming, video conferencing and broadcast on every modern NVIDIA GPU. You will lead the infrastructure and operations for this group’s work. This includes setting up compute resources on-premises and in the cloud. You will develop distributed pipelines for large-scale regressions and experiments across hardware simulations and machine learning workloads. You will maintain the CI/CD and development environments. You will also transform one-off research workflows into reliable, repeatable, automated systems. This is a hybrid role — 4 days per week from the office. What You'll Be Doing - Work closely with our Architects and Algorithms Engineers to understand the needs and transform one-off research workflows into dependable, consistent, automated systems - Stand up and operate the compute the group runs on — on-prem GPU clusters, cloud bursts, queues, schedulers (Slurm / Kubernetes), container images, environments - Develop and build decentralized workflows for extensive regression testing and experiments across HW-simulations and ML workloads — and the dashboards that make sense of the results - Lead the team’s CI/CD plus the dev environments, container images and tooling everyone in the group lives in every day What We Need To See - B.Sc. in Computer Science or Electrical/Computer Engineering - 5+ years in a DevOps, SRE, MLOps, Research-Ops or platform-engineering role - Strong Linux fundamentals — shell, processes, networking, filesystems, systemd, performance tools - Strong hands-on experience in Python — confident writing production-quality code, not just scripts - Hands-on experience with at least one major Cloud ecosystem (OCI, AWS, Azure, GCP) and with Infrastructure as Code (Terraform, Pulumi or similar) - Containers and orchestration: Docker plus Kubernetes, and/or HPC schedulers like Slurm - Experience designing and bringing up CI/CD flows at scale (GitLab CI, GitHub Actions, Jenkins or similar) and operating distributed batch pipelines Ways To Stand Out From The Crowd - Familiarity with video compression / codecs (NVENC, NVDEC, FFmpeg, GStreamer) - GPU-aware infrastructure experience: CUDA toolkit installs, driver versioning, MIG, NCCL - Reading-level comfort with C++ — enough to debug a build or trace a benchmark issue into the codec stack - Observability experience — Prometheus, Grafana, OpenTelemetry, structured logging NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is a world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, NVIDIA has been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the world's hardest problems. We are now looking for a Solution Architect to work with enterprise companies in Japan and partners , promoting the adoption and providing technical support to enable them to use our portfolio of GPU-accelerated computing solutions—including machine learning, deep learning, and especially generative AI . In Japan, the development of sovereign AI and agent-based systems using it is rapidly progressing. We are looking for people who are interested in pre-sales and technical support activities involving support and proposals for those model training and deployment. W e need a passionate, hard-working, and creative individual who has the skills and aims to work in a fast-evolving technological environment that is always on the cutting edge of AI and Accelerated Computing. This individual is self-driven , excellent in communication and partnership, stays on top of tasks, mission focused and outcome oriented. What you'll be doing: - Develop and demonstrate solutions based on NVIDIA’s pioneering GenAI software and hardware technologies with a focus on inference. This may include advising our customer on agent-based system design and optimal models and infrastructure. - Work directly with key customers to understand their challenges and provide the best solutions based on NVIDIA products - You will drive sustainability by performing in-depth analysis and optimization to ensure the best performance and cost-effectiveness using the NVIDIA software platform. This includes transitioning pipelines to lower precision compute . - Drive pre-sales conversations, build architectures and demos to accelerate the customer AI journey based on NVIDIA products, and work closely with Sales Account Managers to secure design wins. - Create or run Proofs of Concept and demos that require presentation skills, the explanation of complex topics, and Python coding to execute data pipelines, train ML/DL models, and deploy them on container-based orchestrators . What we need to see : - Excellent verbal, written communication, and technical presentation skills in Japanese.  Business level English communication is also a requirement. - BS or MS in Computer Science, Engineering , Mathematics , or Physics (or equivalent experience) - 5+ years of industry or academic experience related to Generative AI or Deep Learning - Strong coding development and debugging skills. Including experience with Python, C/C++, Bash, and Linux - Demonstrated experience with cluster orchestration tools including Docker, Kubernetes, or SLURM across cloud service providers and on premises - Ability to multitask effectively in a dynamic environment - Strong analytical and problem-solving skills - Clear written and oral communication skills with the ability to effectively collaborate with management and engineering - Have a strong desire to share knowledge with clients, partners and co-workers Ways to stand out from the crowd: - Expertise in deploying large-scale training and inferencing pipeline - Experience with pre- training, post-training of transformer-based architectures for language or vision - A deep understanding of the latest generative AI or deep learning methods and algorithms - Experience using or operating Kubernetes, as well as experience writing or customizing Kubernetes configurations - Experience in designing agent-based systems: Experience working as an architect on the overall design, including optimal infrastructure, agent architecture, and authentication systems NVIDIA is widely considered to be one of the technological world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is looking for a Senior HPC & AI Operation Engineer to join the Networking clusters solutions HPC/AI Infrastructure team. We are building supercomputers and AI clusters based on groundbreaking technologies. We are looking for a system administrator to be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. Does this sound like you? If so, we would love to hear from you! What you will be doing: - Deploy, manage and maintain large scale HPC/AI clusters - Managing Linux job/workload schedules and orchestration tools - Support and maintain continuous integration and delivery pipelines - Troubleshooting and fixing, bottom up from bare metal, operating system, software stack and application level - Supporting Research & Development activities and engaging in POCs/POVs for future improvements What we need to see: - Bachelor's Degree in Computer Science, Engineering, or a related field; or equivalent experience - 5+ years of experience - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software - Experience with job scheduling workloads and orchestration tools such as Slurm, K8s - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalls, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. - Python programming and bash scripting experience, automation and configuration management tools such as Jenkins, Ansible, Gitops - Knowledge of Networking Protocols like InfiniBand, Ethernet - Experience with virtual systems (for example VMware, Hyper-V, KVM) - Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud) Ways to stand out from the crowd: - Knowledge of CPU and/or GPU architecture - Knowledge of Kubernetes, container related microservice technologies - Experience with GPU-focused hardware/software (DGX, Cuda) - Background with RDMA (InfiniBand or RoCE) fabrics NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. We have a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all IL-Hybrid

NVIDIA's groundbreaking invention of the GPU in 1999 not only sparked the growth of the PC gaming market but also redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning has ignited the modern AI era, positioning the GPU as the brain behind computers, robots, and self-driving cars that can perceive and understand the world around them. NVIDIA is seeking a Customer Solution Architecture and Application Engineering Manager to join our team. In this pivotal role, you will collaborate with our key hardware design teams to enable NVIDIA's next-generation Embedded products and system solutions. Your responsibilities will include leading a Partner Enablement team to ensure product quality and reliability, optimize system performance, and enhance the integration process. You will engage with customers from New Product Introduction (NPI), design integration, and validation stages, all the way through to mass production deployment. This is a unique opportunity to lead Embedded solutions into the fastest-growing markets, including artificial intelligence, deep learning, and advanced computing! We have a rare chance to change the world with our next-generation solutions at the forefront of advanced technology, making a significant impact on our daily lives. If you are passionate about technology that drives growth in AI markets and want to be part of a diverse team that is making a difference, we encourage you to apply now to join NVIDIA! What You’ll Be Doing: - Lead a team to collaborate with major Tier-1 and key OEM customers, as well as internal teams, to develop future Embedded architectures and roadmaps. - Lead a team working alongside hardware design, firmware, software, sensors validation and AI algorithm teams to integrate NVIDIA's Embedded solutions into our customers’ products. - Define system-level requirements and specifications for Embedded architectures using NVIDIA SoC solutions, while maintaining design documentation, test plans, and other customer enablement materials. - Evaluate and enhance system performance, power efficiency, and thermomechanical integration, while simultaneously providing internal teams with laser-focused feedback for future improvements. - Lead a team to address complex technical design issues at all levels. - Collaborate with multi-functional teams at NVIDIA to ensure customer solutions are extraordinarily optimized to be the highest-performing solutions in the world. What We Need to See: - Expertise in thermal, mechanical, and electrical (TME) engineering, with experience ranging from nano-electronic and micro-mechanical board design to the integration of large-scale Automotive and Robotic systems. - 10+ overall years of proven experience and 3+ years in a management role. - BS or equivalent degree in EE/CE/CS engineering field or equivalent experience - Consistent track record of leading a team and working with multidisciplinary groups (hardware, firmware, software, validation, project management, sensors, and AI algorithm developers). - In-depth knowledge of AI hardware products and applications. - Exceptional communication skills, both external and internal, coupled with strong collaboration abilities. - A deep passion for complex problem-solving on a technical and process level, while comprehending the broader implications and trade-offs involved. NVIDIA offers highly competitive salaries and a comprehensive benefits package. Our team comprises some of the most experienced and dedicated individuals in the world, and due to outstanding growth, our extraordinary engineering teams are growing rapidly. If you are a creative and autonomous engineer with a genuine passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 196,000 USD - 310,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to hardware design and system software development. The role of a Deep Learning Systems Engineer would be to analyze the performance and power consumption of deep learning applications on datacenter-class hardware and significantly influence the design and optimization of datacenters. Do you want to influence the development of high-performance Datacenters designed for the future of AI? Do you have an interest in system architecture and performance? In this role you will find how CPU, GPU, networking, and IO relate to deep learning (DL) architectures for Natural Language Processing, Computer Vision, Autonomous Driving and other technologies. Come join our team, and bring your interests to help us optimize our next generation systems and Deep Learning Software Stack. What you'll be doing: - Help develop software infrastructure to characterize and analyze a broad range Deep Learning applications - Evolve cost-efficient datacenter architectures tailored to meet the needs of Large Language Models (LLMs). - Work with experts to help develop analysis and profiling tools in Python, bash and C++ to measure key performance metrics of DL workloads running on Nvidia systems. - Analyze system and software characteristics of DL applications. - Develop analysis tools and methodologies to measure key performance metrics and to estimate potential for efficiency improvement. What we need to see: - A Bachelor’s degree in Electrical Engineering or Computer Science or equivalent experience (Masters or PhD degree preferred). - 8 years or more of relevant experience. - Experience in at least one of the following: - System Software: Operating Systems (Linux), Compilers, GPU kernels (CUDA), DL Frameworks (PyTorch, TensorFlow). - Silicon Architecture and Performance Modeling/Analysis: CPU, GPU, Memory or Network Architecture - Experience programming in C/C++ and Python. Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm) is a plus. - A deep understanding of computer system architecture and performance analysis is essential for success in this role. Applicants should have demonstrated hands-on experience in these domains. - Demonstrated ability to work in virtual environments, and a strong drive to own tasks from beginning to end. Prior experience with such environments will make you stand out. Ways to stand out from the crowd: - Background with system software, Operating system intrinsics, GPU kernels (CUDA), or DL Frameworks (PyTorch, TensorFlow). - Experience with silicon performance monitoring or profiling tools (e.g. perf, gprof, nvidia-smi, dcgm). - In depth performance modeling experience in any one of CPU, GPU, Memory or Network Architecture - Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm). - Prior experience with multi-site teams or multi-functional teams. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Do you want to help drive the development of CPU architectures to fuel the explosive growth in artificial intelligence (AI) / deep learning (DL), high-performance computing (HPC), gaming, virtual reality, and autonomous vehicles?  Come join the CPU performance architecture team as a Senior System Simulation Architect and help us push performance boundaries for NVIDIA’s line of CPU products! What you’ll be doing: - Develop full-system functional models capable of running complex multi-threaded heterogeneous (CPU/GPU) workloads – with special focus on the CPU subsystem. - Integrate functional models from various frameworks with RTL simulators and emulators, hardware (HW-in-the-loop), and detailed performance models. - Bring up system and application software in simulation and emulation – including firmware, Linux, drivers, benchmarks, and CPU/GPU workloads such as deep-learning (DL) and high-performance computing (HPC) workloads. - Port/extend/develop system software (firmware, OS, and drivers) to meet workload simulation needs. - Support CPU architects and performance engineers in their use of functional models, performance models, and emulation to drive next-generation CPU architectures. What we need to see: - BS/MS in EE, CE, or CS or equivalent experience - 6 or more years of relevant experience - Excellent C/C++/Python programming skills - Experience in development of functional simulators and/or low-level software (OS, firmware, drivers); preferably both - Excellent debugging skills – of both system software/firmware and application software - Experience with the ARM ISA - Excellent communication and teamwork skills Ways to stand out from the crowd: - Experience working with hardware emulators and/or FPGAs - Background in CPU workload analysis (SimPoint, etc.) - Experience with Linux kernel bringup and debug - Familiarity with CUDA - Experience with CPU/GPU application development and optimization in Pytorch, TensorFlow, and similar frameworks NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries — from robotics and autonomous vehicles to healthcare and climate research. With the introduction of the Grace CPU Superchip, and more recently, the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA’s broader technology stack, enabling faster AI model training, agentic use-cases, efficient data processing, and scalable cloud deployments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a Senior Accelerated Computing Architect! NVIDIA is developing software and system architectures for accelerated high performance computing, scientific computing, machine learning, AI, datacenter, and automotive computing. This position offers you the opportunity to make a meaningful impact in a fast-moving, technology focused company. What you'll be doing: - Performing in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs. - Creating and optimizing core parallel algorithms, data structures, and reference codes to provide the best possible solutions for NVIDIA GPUs. - Understanding and analyzing the interplay of hardware and software architectures on core algorithms, programming models, and applications. - Actively collaborating with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing. - Diving into accelerated computing applications to facilitate software-hardware co-design. - Writing up and presenting your work by writing white papers, conference publications, official blog posts, patent applications, etc. as appropriate. What we need to see: - An MS or Ph.D. in Computer Science, Computer Engineering or Electrical Engineering, or equivalent experience - 6+ years of relevant work experience - Strong mathematical fundamentals, including linear algebra and numerical methods. - A passion for performance optimization. - Hands-on experience with the massively parallel GPU programming model, e.g. CUDA or OpenCL. Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM, is a plus. - Strong knowledge of C and C++ with solid understanding of software design, programming techniques, and algorithms.  Familiarity with threading APIs for multicore CPUs and Unix-style Inter-process Communication (IPC) APIs is a plus. - Familiarity with Python is a plus. - Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills. - Experience benchmarking, profiling characterizing workloads on GPU and CPU clusters. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of pushing an architecture to its limits? If so, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

In this role, you will be a contributing member of the OEM AI Factory SA team. Our work encompasses MEP (Mechanical Electrical Plumbing), Ethernet and Infiniband networking, DevOps, HPC/AI workloads, Cluster Administration and Site Reliability Engineering. You will acquire insight into various facets of AI Factories deployments. Applicants should be familiar with Linux system administration, Python, and networking concepts. Solid understanding of Slurm and data sciences is a plus. Our Team is responsible for OEM AI factory build engagements - which means that we work with our OEM partners (Dell, HPE, Lenovo and others) to use NVIDIA solutions integrated in their platforms. NVIDIA certified servers include GB200/300 NVL72, along with our software stack that assists with the deployment, configuring, validating and monitoring for the AI Factories of the future. What you’ll be doing: - Collaborating with solution architects, engineering or product teams! - Understanding technical needs of partners and customers - Developing proof of concept projects with NVIDIA technologies. - Assisting with key takeaways, documenting and sharing. - Educating our Partners through hands-on trainings. What we need to see: - BS, MS, or PhD in Computer Science, Computer Architecture, Electrical Engineering, Math, Physics, Data Science, or related technical fields (or equivalent experience) - 5+ years experience - Strong skills in one or more programming languages (Python, C, C++, etc.) - Excellent presentation, communication and collaboration skills - Ability to work independently and with a cross-functional team - Comfortable multi-tasking in a fast-paced environment with changing requirements - Strong analytical and problem-solving skills Ways to stand out from the crowd: - Experience with NVIDIA GPUs and software libraries - Work experience within an engineering or research community - A computer architecture, software engineering, or data science foundation - Academic or industry familiarity with GPUs, AI, CUDA, or related technologies - Ability and eagerness to dig into unfamiliar territories to take on problems relying on experience from previous work with data center infrastructure experience, from hardware up through technology stack NVIDIA is renowned as one of the most coveted employers in the tech world. We’re home to some of the industry's brightest and most innovative minds. If you’re excited about witnessing how a global technology leader stays at the cutting edge, we'd love to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing! An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company. IPP is a global organization within NVIDIA. The group works with various other teams within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs. As a senior engineer on AI Workflow, you will create and establish tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across NVIDIA. What you’ll be doing: - Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability - Experience designing, developing, and deploying AI agents to automate software development workflows and processes. - Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR). - Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures. - Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge. What we need to see: - BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience. - Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development - Strong background in implementing AI solutions to solve real-world software engineering problems. - Hands-on experience on Python/Java/Go with extensive python scripting experience. - Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch. - Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL). - Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools. - Good understanding of distributed systems, understanding of microservice architecture and REST APIs. - Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams. Ways to stand out from the crowd: - Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges. - Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize. - Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data. We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. We are building a team that will truly change the world. If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, we would love for you to join us.

Join our team at NVIDIA and help bring AI solutions to our largest customers. We are seeking an expert Solutions Architect to assist customers in building AI/ML and HPC software solutions at scale. As a member of our Solutions Architecture team, you will collaborate with strategic customers, providing end-to-end technology solutions and technical support based on our product strategy. Come join us! What you’ll be doing: - Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies. - Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions. - Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference. - Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions. - Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers. - Analyzing and developing solutions for customer performance issues for both AI and systems performance. What we need to see: - BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience. - 8+ years of engineering (performance/system/solution) experience. - Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference. - Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application. - Effective engineering program management with the capability of balancing multiple tasks. - Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments. Ways to stand out from the crowd: - Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.). - Familiarity with deep learning architectures and the latest LLM developments. - Background with NVIDIA hardware and software, performance tuning, and error diagnostics. - Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking. - Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We're looking for a Senior Performance Compiler Engineer to join our team and work on the open-source Triton compiler project. This opportunity involves working with new technologies and using compilers to improve AI performance on NVIDIA GPUs. Your work will enable breakthroughs in large language models, agents, and other high-impact AI applications, accelerating both training and inference. You will be immersed in a diverse, supportive environment where everyone is inspired to do their best work, pushing the limits of what's possible. What you’ll be doing: - Investigating the latest and future NVIDIA GPU hardware architecture and programming models. - Working on the frontier of AI by understanding advanced algorithms (like attention sinks and MoEs) and numerics (like block-scaled floating point) to identify new opportunities for optimization. - Designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions (written in Triton's Python DSL), with a focus on generating efficient, low-level GPU code. When vital, you'll also be able to use inline PTX to hand-tune critical code paths and extract peak performance from the hardware. - Engaging in a dynamic, iterative process of optimization—sometimes starting with the kernel, sometimes with the compiler—to find the most efficient path to peak performance. - Collaborating with teams across NVIDIA, including hardware architects and the CUDA compiler team, to influence future products and ensure we are always operating at maximum efficiency. What we need to see: - Bachelor, Masters or Ph.D. degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or a related field. - 8+ years of relevant industry experience in software development. - Demonstrated strong C++ programming and software design skills, with an emphasis on performance analysis and debugging. - Experienced in parallel programming, including CUDA/OpenCL GPU programming or other parallel models such as OpenMP. - Solid understanding of computer architecture and hands-on experience with assembly-level programming. Ways to stand out from the crowd: - Experience in tuning BLAS or deep learning library kernels. - Background in numerics and linear algebra. - Experience with machine learning compilers like TVM or MLIR. - Contributions to open-source projects, especially in the AI/ML or compiler space. - Familiarity with the latest research in AI algorithms and numerics as well as a strong track record of contributions to open-source projects, particularly in the AI/ML, compiler, or high-performance computing domains. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking a highly skilled and versatile Performance Research and Analysis Manager to join our Performance Group. This role will drive end-to-end performance strategy and execution for next-generation NVIDIA NIC, Switch, and Networking technologies, spanning the full lifecycle from pre-silicon performance modelling (simulation and emulation) through bring-up, validation, and GA readiness. The ideal candidate will lead cross-functional performance efforts across multiple teams to evaluate and optimize low-level networking and offload capabilities, including Storage acceleration, Security protocols, NIC pipeline and steering mechanisms, Switch performance, and E2E AI Networking cluster level performance for AI WLs, distributed training, and Inference jobs. In addition, this role will play a key leadership position in building scalable telemetry frameworks, performance dashboards, and job-level monitoring solutions to enable continuous performance tracking and root cause analysis across NVIDIA supercomputing environments. The position also includes deep ownership of competitive benchmarking and performance analysis. You will work closely with a wide range of NVIDIA hardware and software platforms, including HCAs, DPUs, switches, CPUs, GPUs, and full system architectures, across multiple networking stacks and performance-critical software layers. What you'll be doing: - Lead performance research and evaluation of advanced networking technologies supporting AI workloads, including LLM training and inference at supercomputing scale. - Define end-to-end performance test plans and methodology for next-generation Networking HW and networking technologies, including performance expectations and target KPIs. - Drive benchmarking, profiling, reporting, and deep performance characterization of networking workloads and offload features. - Collaborate closely with simulation, architecture, chip-design, firmware, and software teams to assess performance tradeoffs and identify bottlenecks. - Perform deep root cause analysis (RCA) for performance gaps and stability issues, and drive cross-team mitigation plans. - Develop and enhance performance analysis tools, automation frameworks, and scalable methodologies for cluster-level performance evaluation. - Own performance observability efforts, including telemetry pipelines, dashboards, and job-level performance analytics. What we need to see: - B.Sc in Computer Science or Software Engineering - 5+ years of experience with high-performance Networking technologies (RDMA, Storage, Security, OVS, MPI) - 3+ years as an engineering team manager - Demonstrated Performance Analysis skills and methodologies. - Experience with Cluster level performance, Telemetry, NIC, DPUs, Switches, and GPUs. - Fast and self-learning capabilities with strong analytical and problem solving skills - Programming Languages: Python, Bash and C/C++ languages - Experience with Linux OS distros - Team player and a leader with good communication and interpersonal skills Ways to stand out from the crowd: - Deep system-level architecture knowledge (Intel / AMD / ARM CPUs, NVIDIA GPUs, HCA/DPU architecture, memory subsystems, PCIe, storage, NVLink). - Strong expertise in RDMA networking performance and AI communication stacks (e.g., NCCL). - Proven experience analysing AI workload communication patterns and benchmarking distributed LLM training workloads at scale. - Experience designing telemetry frameworks, monitoring pipelines, and performance dashboards for large clusters. - Familiarity with modern AI tooling including performance-driven agents, automation pipelines, and RAG-based applications. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. LI-Hybrid

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning (DL) software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts focused on Generative AI and Large Language Models (LLMs). You will also collaborate with a diverse set of internal teams on performance analysis and modeling of inference software. You should be comfortable working in a dynamic environment, and have experience with Generative AI, LLMs, and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! What You Will Be Doing: - Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions - Dynamically engaging with developers, scientific researchers, data scientists, which will give you experience across a range of technical areas - Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform - Working closely with customers to help them adopt and build solutions using NVIDIA technology - Analyze performance and power efficiency of deep learning inference workloads - Some travel to conferences and customers may be required What We Need To See: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow - Strong fundamentals in programming, optimizations and software design, especially in Python - Strong problem-solving and debugging skills - Excellent knowledge of theory and practice of Large Language Models and Deep Learning inference - Excellent presentation, communication and collaboration skills - Desire to be involved in multiple diverse and creative projects Ways To Stand Out From The Crowd: - Experience with NVIDIA GPUs and software libraries, such as NVIDIA NeMo Framework , NVIDIA Triton Inference Server , TensorRT , TensorRT-LLM - Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design - Familiarity with parallel programming and distributed computing platforms - Prior experience with DL training at scale, deploying or optimizing DL inference in production Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! What you'll be doing: - You will be working on architecting GPU power features and system level power management solutions for NVIDIA products. - Collaborate closely with other Architects, Software Engineers, ASIC Design Engineers, and Product teams to study, devise and implement the power management strategy for NVIDIA's GPU roadmap. - Research and develop solutions to address complex energy efficiency problems for various GPU use-cases such as: Deep Learning training, ADAS, Gaming, Video Playback, and Idle. - Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs and platforms. What we need to see: - Pursuing or recently completed a MS or PhD in Electrical or Computer Engineering (or equivalent experience) - Knowledge of performance simulators/monitors and Low Power architectures/techniques a plus. - Working knowledge of Python, and frameworks/packages like: TensorFlow, Pandas, NumPy, PyTorch a plus. - Exposure to tools/flows such as Design Compiler, PTPX, and Power Artist etc a huge plus. - Experience with lab setup and measurement using equipment such as scope/DAQ is helpful. Ways to stand out from the crowd: - A master’s degree/internship with a focus/projects in Low Power Architecture, power modeling, and deep learning is a plus! NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Artificial intelligence is moving from passive assistance to autonomous, always-on agentic workflows. Our mission is to make this transition flawless, high-performing, and secure for millions of users worldwide. We are looking for a Senior Engineer to serve as a key technical leader in deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs. You will lead the development to ensure open-source AI agents (like Nemoclaw and OpenClaw) run locally, safely, and efficiently on consumer PCs. By combining powerful local inference (Nemotron models) with robust privacy routers and sandboxed execution, you will help create the foundation of the desktop AI operating system. What You Will Be Doing: - Act as the lead engineer for developing the agent frameworks natively on Windows environments. You will shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops. - Lead the engineering efforts to optimize the agent runtimes for Windows. You will ensure that autonomous agents operate within thorough, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress). - Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community. Ensure our consumer hardware provides an excellent ecosystem for autonomous agents. - Foster a collaborative engineering culture by mentoring other engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code. What We Need to See: - 10+ years of relevant professional software engineering experience, with at least 3+ years in Staff, or Lead Architect role. - BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience). - Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture. - Proven understanding of LLM inference pipelines (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware. - Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools. - Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic). - Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most talented people on the planet working for us. As part of our team, you will have the opportunity to influence the future with your vision and expertise. Are you creative? Are you driven not just by data or the need to know why, but yearn to ask, 'why not'? We want to hear from you. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Are you a visionary at the intersection of AI innovation and executive influence? Do you thrive on shaping the future of visual understanding and AI-driven operational intelligence? If you’re a bold, strategic problem solver with deep technical expertise in modern computer vision, foundation models, and AI agents — this is your opportunity to lead from the front and help redefine what’s possible in the world of Physical AI. As a Senior Developer Relations Manager for NVIDIA Metropolis, you’ll be a key force driving the adoption of next-generation AI technologies that transform how cities, industries, and infrastructure think, see, and act. You’ll engage with innovative ISVs, global enterprise leaders, and ecosystem partners to unlock the full potential of visual understanding and automation. This is your chance to be a trailblazer in an era where perception meets reasoning, helping to accelerate the evolution from traditional AI pipelines to multimodal Vision-Language Models (VLMs) and intelligent agents capable of real-world decision making. What You’ll Be Doing - Identify, build, and guide strategic relationships across the AI ecosystem, from startups to enterprise CEOs, driving real-world adoption of NVIDIA’s advanced Vision AI and VLM capabilities - Engage developers and partners working on video analytics, perception, and AI agent use cases to bring breakthrough use cases to life - Provide hands-on technical leadership, augmenting CNN-based models with Vision Language Model (VLM) architectures into applications for video understanding, safety, operational intelligence, etc. - Partner closely with NVIDIA’s engineering, product, and marketing teams to guide developers and accelerate innovation within intelligent environments - Lead thought leadership discussions and get-to-market strategies to expand NVIDIA’s footprint in next-generation visual computing and AI ecosystems What We Need To See - Deep technical expertise in AI and computer vision, including hands-on experience with CNN architectures, Vision-Language Models (VLMs), and AI agent systems - Proven track record working directly with executive collaborators (C-suite, CTOs, founders) to shape technical strategy and drive measurable business outcomes - Strong background in AI for video understanding, public safety, ITS, industrial operational intelligence, safety compliance, or related domains - 8+ years of experience in technical roles that bridge innovation, strategy, and relationship management - Bachelor’s degree or equivalent experience in Computer Science, Engineering, or related field (Master’s or Ph.D. highly preferred) - Exceptional communication, executive presence, and ability to navigate complex technical and business dynamics Ways To Stand Out From The Crowd - Experience building and deploying AI solutions for physical environments — robotics, manufacturing, intelligent spaces - Familiarity with NVIDIA platforms such as Metropolis, DeepStream, CUDA-X, Omniverse - Proven success in empowering developer ecosystems and accelerating partner adoption in emerging AI fields

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. Come work for the team that brought to you NCCL, NVSHMEM & GPUDirect. Our GPU communication libraries are crucial for scaling Deep Learning and HPC applications! We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: - Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. - Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack - Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available - Triage and root-cause performance issues reported by our customers - Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information - Collaborate with a very dynamic team across multiple time zones What we need to see: - M.S. (or equivalent experience) or PHD in Computer Science, or related field with relevant performance engineering and HPC experience - 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM) - Experience conducting performance benchmarking and triage on large scale HPC clusters - Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) - Implement micro-benchmarks in C/C++, read and modify the code base when required - Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python - Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker) - Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: - Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control - Experience debugging network issues in large scale deployments - Familiarity with CUDA programming and/or GPUs - Experience with Deep Learning Frameworks such PyTorch, TensorFlow NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 221,250 PLN - 383,500 PLN for Level 3, and 292,500 PLN - 507,000 PLN for Level 4.

Step into the future with NVIDIA, a global leader in AI computing, data science, and graphics, driving innovation in Artificial Intelligence, Deep Learning, and Autonomous Vehicles. Our team of visionaries is reshaping industries worldwide with cutting-edge technologies. Join us on an exhilarating journey as a  Senior Software Program Manager  to join our collaborative and fast-paced customer interfacing automotive software organization. In this role, you will be supporting our  Korea n partners closely to integrate, adapt and test our NVIDIA DRIVE Software solutions, including DRIVE OS, NDAS and Alpamayo. NVIDIA is synonymous with innovation, boasting trailblazers who are shaping the world with their forward-thinking approaches. This is your chance to be part of a vibrant community that's redefining the technological landscape. Ready to shape the future of automotive technology with NVIDIA? Apply now to be part of a team that's revolutionizing the industry and driving innovation to new heights. Your potential awaits! What you’ll be doing: - Lead the lifecycle of NVIDIA’s DRIVE programs with our  Korea n automotive partners. Align on timelines and contents for SW deliveries incl. those of NVIDIA’s DRIVE OS, NDAS and Alpamayo software stacks. - Coordinate with cross functional teams in South  Korea , India, China, and the U.S. to resolve program issues and drive product launches. - Act as the first point of contact and first level of escalation for our automotive partners and internal senior leadership, providing updates and bringing management focus on important issues. - Align on program vehicle and system level requirements, coordinate the review, exchange, and negotiation of them. Work closely with internal software groups to understand the design and implementation - Track and prioritize know issues and bugs, allocate fixes to upcoming SW releases, track verification, and root cause analysis. What we need to see: - General knowledge about Artificial Intelligence, LLMs, Transformers, CPU/GPU architectures, etc. - General knowledge of program management concepts (task planning, agile methodologies, risk management, etc.) - Degree from a leading university or equivalent experience in an engineering or computer science related field (BS; MS or PhD). - 6+ years of work experience in automotive software development. Preferably on ADAS and AV. - Understanding of autonomous vehicle systems, sensor technologies, vehicle bus communication standards, SoCs and embedded software principles. - General knowledge of C/C++/Python, QNX and/or Linux OS. - Understanding of build pipelines, repositories, CI/CD, containerization, etc. - Proven experience of having led complex automotive programs to series production. - Excellent communication and organization skills, good time management, and task prioritization . - Willingness to regularly attend customer meetings at NVIDIA's partners’ sites. Ways to stand out from the crowd: - Experience with Automotive SPICE, ISO26262, 21448 standards. - Hands on experience developing complex embedded C++ based systems. - Fluency in  Korea n - A wide existing network of contacts in the local automotive ADAS and AV industry NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and proactive, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.

We are now looking for a Senior Signal & Power Integrity Engineer! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Work on crafting creative Signal Integrity solutions to complex system design problems - System-level signal integrity simulations of high-speed NVlinks 200Gbs+, USB-4, PCIe5, GDDR6, LP5X - Modeling of vias, connectors, sockets and various system components in 3D EM tools. - Design and optimize Power Delivery Network (PDN) across packages and PCBs. - Constant improvements of SI/PI models through lab measurements - Simulation automation, data gathering, analysis and visualization using JMP, MATLAB or similar tools. - Opportunity to work in dynamic cross-functional role to optimize package, PCB, ASIC, mixed signal circuit What we need to see: - BS/MS-Electrical Engineering or equivalent experience. - 3+ years of industry experience. - SI/PI work on one or more signaling standards like PCI express, USB, SATA, HDMI, HBM, DDR5, GDDR6, LPDDR5X - Hands on use of 3-D modeling tools like ANSYS HFSS/Q3D and 2.5-D with ANSYS SIWAVE or similar. - Experience with PDN evaluation using layout extraction tools for packages and PCBs and spice-based time domain simulations. - Background with a system level timing or loss budget including silicon, package and board impairments. - Familiarity  with use of VNA, TDR, DSO, ParBERT and use of applications like JMP, Matlab will be a plus Ways to stand out from the crowd: - Expertise in one or more of the high speed interface SI/PI design on any industry standard system platforms. - Experience with lab measurements, debugging, SI lab correlation using oscilloscope/ spectrum analyzer/ VNA. - Knowledge of circuit design, board/pkg component design,  link architecture, timing budget methodologies LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a Senior Signal & Power Integrity Engineer! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Work on crafting creative Signal and Power Integrity solutions to complex system design problems. - System-level power integrity simulations of high-performance AI systems, graphic cards, and Tegra systems. - Work closely with VLSI power teams and package/board design teams to design, optimize, and model power delivery networks (PDN) including dies, packages, boards, and voltage regulators. - Package and board PDN guidelines creation, review, and post layout PI extractions. - Opportunity to work in a dynamic cross-functional role to optimize package, PCB, ASIC, mixed signal circuit. What we need to see: - Pursuing MS/PhD in Electrical Engineering or equivalent experience. - Strong technical background in applied electromagnetics, transmission line theory, and signal processing is highly valued. - Experience in power integrity for core power or I/O power. - Strong understanding of how die/package/board decoupling impacts power supply noise across different frequency ranges. - Knowledge of on-die current di/dt control techniques such as dynamic clocking and throttling. - Familiarity with the SIMPLIS tool for regulator modeling; experience in modeling the behavior of on-die di/dt control techniques is highly preferred. - Hands-on experience with PowerSI, 3D modeling tools such as ANSYS HFSS/Q3D, 2.5D tools such as ANSYS SIwave (or similar), and 2D tools such as Ansys 2D Ways to stand out from the crowd: - Good understanding of how regulators work and expertise in regulator modeling. - Knowledge of package/board/decoupling capacitor technology & design. - Scripting for analysis automation NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We are looking to grow our company and   establish   teams with the most thoughtful people in the world.  NVIDIA DGX, HGX, and MGX systems deliver the world's leading solutions for enterprise AI infrastructure at scale. We are   seeking   a dedicated and experienced RAS (Reliability, Availability, and Serviceability). Senior Engineer. You will   be responsible for   improving the reliability of NVIDIA GPU and Grace systems by designing, architecting, and implementing robust RAS features. You will collaborate with multi-functional teams, including hardware engineers, system architects, and software developers, to compose architecture that meets strict reliability standards and provides outstanding customer   experiences.  Are you ready to change the next generation of computing?  Join us at the forefront of technological advancement. What you will be doing: - Design, architect, and deliver server-level RAS for NVIDIA’s data center products. - Define RAS requirements that ensure compliance with industry standards and customer expectations for scale-out environments. - Develop fault detection, isolation, and recovery mechanisms to ensure system resilience and minimize downtime. - Evaluate and select appropriate technologies and components to optimize reliability, availability, and serviceability, considering factors such as mean time between failures (MTBF), mean time to repair (MTTR), and total cost of ownership (TCO). - Collaborate with customers, vendors and suppliers to assess and integrate their RAS-related solutions into the overall system architecture. - Conduct system and cluster level simulations, analysis, and testing to validate and verify the effectiveness of the RAS architecture and its components. - Stay up to date with the latest advancements in RAS techniques, fault tolerance mechanisms, and industry trends to guide future system designs. - Work with NVIDIA partners on RAS related architecture and discussions to improve their use of NVIDIA products. - Work on all phases of product development, from product definition, architecture, and design, through implementation, debugging, testing and early customer support. What we need to see: - BS, MS, or PhD or equivalent experience in EE/CS or related field of education with demonstrated experience of 10+ years - Strong python programming in Linux operating environment, strong understanding of Linux kernel internals, strong code review skills. - Extensive knowledge in system-level architecture invention, reliability engineering, and fault tolerance mechanisms, optimizing RAS architectures for complex computing systems, data centers, or critical applications. - Proficient in scale-out architectures, hands on experience are a plus. - Proficiency in system-level simulation tools and methodologies (e.g., fault injection, reliability block diagrams, failure rate analysis). - Excellent problem-solving skills, attention to detail, and the ability to analyze complex system-level issues. - Possess excellent written and oral communication skills, excellent work ethics, a deep sense of collaboration, love to produce quality work and commitment to finishing your tasks every single day. - You are a self-starter who loves to find creative solutions to complicated problems. Ways to stand out from the crowd: - Consistent track record of doing RAS at platform level - Familiar with In-depth understanding of the interaction of machine check architecture and error flows with system firmware/software. - Hands on with x86 or ARM system architecture. NVIDIA is widely considered to be one of   the technology   world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

We are now looking for a Senior Software Engineer for AI Resiliency! At NVIDIA, we are pushing the boundaries of what’s possible in AI. We are currently seeking a Senior Software Engineer to lead the development of AI software resiliency for the most powerful AI supercomputers in the world. As a member of our AI Software Resiliency team, you will play a pivotal role in defining and implementing critical resiliency features for AI supercomputers at a scale of 100,000+ GPUs. Your expertise will be crucial in driving down cluster downtime towards zero, ensuring that our AI systems remain robust and reliable at all times. What You’ll Be Doing: - Develop AI Software Resiliency Features: Implement and optimize software features that improve AI system reliability at a massive scale, such as fast checkpoint-recovery, error detection, error isolation, and straggler/hang detection. - Hands-On Coding & Optimization: Contribute to large-scale distributed systems with high-quality, production-level C++ and Python code. Enhance performance for AI workloads running on thousands of GPUs. - Fault Tolerance & Debugging: Work on AI system error handling, implementing techniques to detect silent data corruption (SDC) and other failure scenarios. Assist in developing monitoring tools for proactive failure mitigation. - Collaborate Across Teams: Work closely with senior engineers, AI researchers, and hardware/software teams to integrate resiliency features into AI frameworks like PyTorch and JAX/XLA. - Testing & Automation: Develop and implement tests to ensure robustness, scalability, and efficiency of resiliency mechanisms. Contribute to CI/CD pipelines to automate validation of AI workloads. - Support Production Deployments: Assist in debugging and performance tuning large-scale AI workloads in cloud and HPC environments, ensuring seamless operation of AI training and inference workloads. What We Need to See: - You've achieved a Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience. - Proficiency in C++ and Python , with experience in writing efficient, high-performance code. - 6+ years of relevant experience - Strong understanding of distributed systems concepts , parallel programming, and fault tolerance in large-scale computing environments. - Familiarity with AI frameworks such as PyTorch, JAX/XLA, TensorFlow, or similar. - Experience with debugging and profiling tools (e.g., gdb, perf, valgrind, NVIDIA Nsight). - Excellent problem-solving skills and ability to work in a fast-paced, highly collaborative environment. Ways to Stand Out From the Crowd: - Hands-on experience in training models or working with model training teams . - Hands-on experience with CUDA, NCCL, or MPI for GPU-accelerated computing, especially at extreme-scale . - Knowledge of checkpointing strategies, error mitigation, or fault-tolerant computing in AI training. - Experience working with large-scale AI clusters, HPC environments, or cloud-based AI workloads . - Strong systems programming skills and experience with low-level performance tuning. As part of the AI Resiliency team at NVIDIA, you’ll work alongside world-class engineers solving some of the hardest challenges in AI infrastructure. You’ll have the opportunity to contribute directly to making AI training and inference more reliable, scalable, and efficient. If you're passionate about AI, distributed systems, and high-performance computing, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a motivated Physical Design Engineer to join our dynamic and growing team. If you want to challenge yourself and be a part of something great, join us today! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing! More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new opportunities which are hard to tackle, that only we can pursue, and that matter to the world. This is our life's work, to amplify human inventiveness and intelligence. What you'll be doing: - Drive physical design and timing from netlist to gds. - Partner with mixed signal teams to integrate Analog IO’s and macros. - Work on multi-mode and multi-corner timing closure, RC extraction, Cross talk, IR drop and EM analysis. - Work with the Front-end teams to create and update timing constraints. - Perform Physical verification DRC, ERC, LVS, Antenna checks and other checks. - Debugging timing violations and implementing functional, Timing ECO’s and perform formal verification. What we need to see: - BS (or equivalent experience) in Electrical or Computer Engineering with 5+ years' experience or MS (or equivalent experience) with 2+ years' experience in physical design. - Experienced in Synopsys or Cadence place and route, physical design and timing tools. - Ability to form methodologies and automate flows. - Scan insertion and DFT knowledge is a plus Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative! What you’ll be doing: - Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization. - Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems. - Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms. - Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware. - Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points. - Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors. - Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues. What we need to see: - MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 6 years of relevant experience. - Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency. - Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation. - Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations. - Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX. - Solid understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors. - Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements. - Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams. - Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads. Ways to stand out from the crowd: - Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale. - Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability. - Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar. - Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments. LI-Hybrid

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world. Join us at the forefront of technological advancement. We are looking for a Senior Circuit Methodology Engineer that will work closely with Nvidia's circuit design engineering team in the area of infrastructure support as it pertains to circuit design and methodology. The engineer will own and evolve the compute and GPU infrastructure in coordination with our Farm, IT, CAD, and GPU infrastructure teams. The stability and management of these resources underpins our mixed‑signal design and verification flows. This position carries a critical responsibility across the whole circuit design department and impacts the whole company’s farm infrastructure! What you'll be doing: - We need someone who will design, develop, and maintain circuit design and verification flows that run on large‑scale compute and GPU farms located across geographies through various job schedulers. These responsibilities will include: - Proactively monitor farm health and job behavior, identify bottlenecks, and implement solutions to improve throughput, utilization, and turnaround time. - Bring up and release new compute and GPU infrastructure to be used by the team. - Evaluate and qualify new compute and GPU resources, schedulers, and related EDA infrastructure components. - Build automation and tooling to streamline flow setup, job submission, resource allocation, logging, and reporting. - Track important measurements (utilization, queue times, failure rates) and lead ongoing improvement projects for farm efficiency and cost effectiveness. - You would also be required to provide user support, which may include: debug flow, infrastructure, and job‑scheduling issues; root‑cause failures; and implement permanent fixes rather than one‑off workarounds. - Additionally, you will be asked to develop and maintain documentation, training materials, and best‑practice guidelines for users of the circuit design compute and GPU environment. We also want to proactively include information into our in-house Ais in order to provide first pass user assistance. What we need to see: - BSEE, BSCE or equivalent experience. - Mid-level of programming skill is a must (primarily Python and Perl). - 8 plus years of working experience related to circuit design methodology using Cadence/Synopsys based system (Virtuoso/Custom Compiler, respectively). Previous design experience is a huge plus. - Experience with job schedulers / compute farms, primarily LSF and Slurm. - Proven ability to debug complex multi-layer issues spanning flows, scripts, tools, and infrastructure. - Strong communication skills and ability to partner with diverse engineering teams. - Exposure to circuit design workloads will be beneficial. NVIDIA is renowned as the leader in AI computing and one of the world’s most innovative and desirable employers. MSDV team consists of individuals who demonstrate outstanding creativity and critical thinking skills, driving innovation forward. If you're passionate, creative, and eager to work on the cutting edge of technology, this is the perfect team for you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for Signal & Power Integrity Engineer. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Drive board/system level signal and power integrity requirements - Lead board/system SI/PI design activities, including PCB stackup/material selection, design guide implementation, layout review, and post-layout analysis - Work closely with Architecture, ASIC, Mixed Signal, Package, and PCB Design teams to design and ensure system SI/PI performance meets expectation before Gerber out, also work closely with Design Validation teams to support SI/PI failure analysis - Develop novel algorithms & new methodologies to improve SI/PI modeling efforts - Work with Application Engineering teams to support customers w/ SI/PI questions - VNA & TDR measurements to support model correlation efforts and improve confidence in design stage What we need to see: - MS/BS in EE or equivalent experience - Minimum 1+ years of experience as a SI/PI engineer - Deep understanding of electromagnetic, specifically electromagnetic waves including transmission line theory and via properties - Proficient with HFSS, Sigrity, Hspice, and/or other simulation tools - Experienced with Cadence Allegro PCB designer and Constraints Manager - Understanding of high volume manufacturing variations and impact to channel signal integrity - Exposure to lab measurements including VNA & TDR experience - Passionate about SI/PI work - Good written & verbal interpersonal skills in English Ways to stand out from the crowd: - Familiarity with NRZ/PAM-4 signaling schemes - Exposure to interface timing budgets and system modeling - Familiarity with high-speed I/O design concepts including clock generation, transmitter & receiver design, and equalization schemes - PDN analyses including model generation and time domain simulation - Experience w/ Matlab, Python, and C as well as exposure to package design

We are seeking a Deep Learning Research Engineer to join our team and help develop the next generation of Large Language Model (LLM) inference algorithms. You will work on technologies that directly enhance NVIDIA's software, making the latest LLMs more efficient and accessible to users worldwide. This role is designed for someone with strong research foundations who also wants to build software that runs and scales into production systems across the world. By joining us, you will be part of a strategic effort to establish NVIDIA as the definitive platform for high-performance LLM inference. The work requires a combination of research taste, experimental rigor, and engineering ownership: you will explore new ideas, run rigorous evaluations, and help transform successful approaches into tools and implementations. What you'll be doing: - Develop and improve benchmarks, profiling workflows, and evaluation pipelines that make inference performance measurable and reproducible. - Design and lead the development of experimental frameworks that enable rapid, reproducible evaluation of algorithmic tradeoffs across quality, latency, throughput, and more. - Prototype new algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios, translating them into practical software solutions that directly impact NVIDIA's products and customers - Trace and profile the performance of new algorithms on NVIDIA’s latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations. - Collaborate with internal research, engineering, and product teams across the globe to drive the development of advanced inference technologies. - Stay ahead of research in LLM inference, efficient generation, model architecture, inference engines, and translate relevant advances into practical solutions. What we need to see: - MSc in Computer Science, Electrical Engineering, or a closely related field; or equivalent experience in an industrial research role. - At least 5 years of proven experience in applied research, research engineering, or algorithm engineering. - Excellent software engineering skills, particularly in Python and deep learning frameworks like PyTorch. - Proven experience with High-Performance Computing (HPC) environments, including training or running inference on large-scale GPU clusters (tens to hundreds of GPUs). - Interest in the systems side of deep learning, including inference engines, benchmarking, profiling, GPU efficiency, memory behavior, and deployment constraints. - A strong problem-solving mentality and a proactive attitude, driven by the ambition to deliver solutions with real-world impact. Ways to stand out from the crowd: - At least one publication in a top-tier AI/ML conference (e.g., NeurIPS, ICLR, ICML). - Deep understanding of LLM architectures coupled with hands-on experience in training large-scale models. - Hands-on research experience in LLM inference optimization algorithms such as speculative decoding or parallelization strategies. - Deep familiarity and experience with popular LLM inference frameworks (e.g., vLLM, TensorRT-LLM). We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

We are looking for an experienced system engineer, who will play a dual role on the NVIDIA Enterprise Experience (NVEX) team. An awesome candidate is highly technical who can triage customer software issues and resolve customer problems as well as someone who can develop key enhancements and tools for the DGX Platform Software, Container Orchestrators, Deep Learning containers, and potentially other Enterprise related system software. This individual should have proven grasp of platform and systems engineering who understands Linux internals, knowledge about servers and has the ability to resolve hardware and/or OS internal issues. If you have a real passion for technology, and you are interested in a role that you can make a difference in and contribute at all different levels, this may be a phenomenal position for you. What you'll be doing: - Develop features and tools as part of solution engineering efforts to support all Enterprise Service offerings including, but not limited to DGX, NVAIE, Container Orchestrators (such as Kubernetes), GPU accelerated applications, and Deep Learning frameworks. - Work with NVIDIA Enterprise customers and internal users to improve the availability, reliability, and overall experience of working with NVIDIA Deep Learning Framework containers on NVIDIA GPUs. - Take ownership and drive customer issues on containers, Deep Learning frameworks, and Cloud deployment from inception to resolution. - Build upon the opportunity to research new use cases with GPUs for emerging container technologies and Deep Learning frameworks. - Bring independent analysis, communication, and problem-solving to customer experience. - Be on call one weekend per month in the event a customer has a Sev1 outage and requires engineering assistance. What we need to see: - BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience). - At least 5 years system software development and troubleshooting experience, ideally with some customer facing. - Intellectual curiosity, positive attitude, flexibility, analytical ability, self-motivation, and team-oriented. - Strong computer science concepts and excellent knowledge of Python and scripting methodologies. - Deep understanding of at least two of the following: data centers, servers, distributed systems, virtualization, deep learning frameworks, containers/containerization (ie Docker, Kubernetes), hybrid cloud (ie AWS, GCP). - You'd have cultivated a deep Linux knowledge, and be very comfortable working in various Linux environments as well as with Windows OS’s. - Professional-level communication skills, interpersonal skills with a passion to solve problems. Ways to stand out from the crowd: - Proven experience in developing, triaging and debugging on Linux and Containers and deep learning frameworks. - Experience working with distributed systems especially container orchestrators. - Any exposure to system level debug and triaging experience. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are expanding fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you.

NVIDIA is looking for a Data Center Deployment Specialist to join its Professional Services team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest data centers in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. As a Data Center Infrastructure Specialist, you will be interacting with customers, partners, and internal teams, to analyse, define and implement large scale Datacenter projects. The scope of these efforts includes a combination of Datacenter Infrastructure design and cluster deployment planning. What you will be doing: - Design and implement flawless data center infrastructure solutions to meet the needs of our customers. - Collaborate with cross-functional teams to ensure the successful deployment of data center infrastructure. - Datacenter Planning: Floor Plan, Rack Elevation, Simulation - Cable deployment planning including - ensuring requirements are accurate such as number and type of connections, port assignments, and timing of activity while following standard methodologies, Point-to-Point Design. - Deploy and Support NVIDIA products. - Validating and updating all related work instructions for Datacenter activities. - Responsible for providing input for Data Center Standards updates as required; balancing multiple activities and priorities; participate in projects calls. - Documenting processes and keeping event logs. - Escort and oversee on-site work delivered by partners and third-party vendors. What we need to see: - 5+ years of proven experience as a data center infrastructure engineer, field service engineer or similar with background in designing and implementing data center infrastructures. - Bachelor's degree or equivalent experience in a relevant field. - In-depth knowledge of data center environments, servers, and network equipment. - Extensive experience in installing, monitoring, and maintaining data center equipment. - Solid understanding of networking, storage, and virtualization technologies. - Excellent problem-solving skills and attention to detail. - Ability to work as part of a team, in a fast and highly dynamic environment. - Exceptional communication and interpersonal skills. - Proficiency in documenting processes. - Willingness to travel. Way to stand out from the crowd: - Network certification such as: Cisco Certified Network Associate (CCNA), Juniper Networks Certified Associate - Junos (JNCIA-Junos) - Knowledge with InfiniBand Technology - Collaboration with R&D and network engineering teams. - Outstanding interpersonal skill. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world, working for us. Our commitment to pushing boundaries and delivering exceptional solutions is unparalleled. As a Data Center Infrastructure Specialist, you will play a key role in shaping the future of computing and driving the success of our clients. At NVIDIA, we are an equal opportunity employer. We value diversity and are committed to creating an inclusive and supportive work environment for all employees. If you are a proactive and driven individual, creative with a strong interest in current technology trends, this is the opportunity you have been waiting for. Join us at NVIDIA and be part of our journey to shape the future of computing. Apply now and let's work together to make a difference!

NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems. NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing: - Develop and maintain continuous integration and delivery pipelines . - Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources. - Deploy monitoring solutions for the servers, network and storage. - Perform troubleshooting bottom up from bare metal, operating system, software stack and application level. - Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research & Development activities and engage in POCs/POVs for future improvements . What We Need To See: - BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture. - 5+ Years of Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools. - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software. - Direct design, implementation and management experience with cloud computing platforms (e.g. AWS, Azure, Google Cloud). - Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes and Singularity. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. - Python programming and bash scripting experience. - Comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet/Chef, etc. - Deep knowledge of Networking Protocols like InfiniBand, Ethernet Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix). - Strong written, verbal, and listening skills in English are critical. Ways To Stand Out From The Crowd: - Knowledge of CPU and/or GPU architecture . - Knowledge of Kubernetes, container related microservice technologies. - Experience with GPU-focused hardware/software (DGX, CUDA.) - Background with RDMA (InfiniBand or RoCE) fabrics. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.

NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems. NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing: - Develop and maintain continuous integration and delivery pipelines . - Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources. - Deploy monitoring solutions for the servers, network and storage. - Perform troubleshooting bottom up from bare metal, operating system, software stack and application level. - Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research & Development activities and engage in POCs/POVs for future improvements . What We Need To See: - BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture. - 5+ Years of Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools. - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software. - Direct design, implementation and management experience with cloud computing platforms (e.g. AWS, Azure, Google Cloud). Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes and Singularity. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. - Python programming and bash scripting experience. Comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet/Chef, etc. - Deep knowledge of Networking Protocols like InfiniBand, Ethernet Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix). - Strong written, verbal, and listening skills in English are critical. Ways To Stand Out From The Crowd: - Knowledge of CPU and/or GPU architecture . - Knowledge of Kubernetes, container related microservice technologies. - Experience with GPU-focused hardware/software (DGX, CUDA.) - Background with RDMA (InfiniBand or RoCE) fabrics. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by extraordinary technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. NVIDIA is searching for an AI/ML Solutions Architect focusing on Hyperscale customers and Cloud Service Providers. Your primary responsibilities will be to lead software customer technical engagement for AI training, inference and infrastructure being deployed at vast scale. You will work across multiple organizations within NVIDIA as well as at the customer to ensure successful and trouble-free deployments. If you would you like to partner with a large company to build automation and management to create a robust large scale artificial intelligence infrastructure and are interested in the optimization and characterization of customer specific AI models and pipelines - you should apply! What you’ll be doing: - As a key technical member of a focused account team, you will serve as the main point of contact for NVIDIA products, enabling internet giants and cloud providers to have an innovative AI/ML software infrastructure. - Work directly with best-in-class engineering teams to secure design wins, address challenges, bring solutions to production, and support them throughout their lifecycle. - Become a trusted advisor to your customer by understanding their environment, constraints, and long-term strategy. Translate these insights into product requirements and innovative solutions. - Help your customer enhance the value of NVIDIA technology, and provide feedback to NVIDIA for future product improvements. - Facilitate the resolution of customer issues, offering timely and proactive communications to mitigate risks. - Lead workshops, demos, and proof-of-concepts to showcase NVIDIA’s AI/ML capabilities. - Guide customers on standard processes for scalable AI model deployment and inference optimization. What we need to see: - Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience. - 8+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions. - Proven understanding of Linux, including solving, optimization, and customization for AI/ML workloads. - Strong understanding of data science and machine learning infrastructure—software and hardware. - Professional-level communication skills, including the ability to tailor messages for varying technical audiences and maintain composure in high-pressure situations. - Excellent follow-up and interpersonal skills, with a true passion for problem-solving. - Proficient in Python, with the ability to develop scripts and build custom tools. Experience with parallel programming or GPU acceleration (e.g., CUDA) is helpful. - Shown eagerness to learn and apply new technologies. Ways to stand out from the crowd: - Experience with Chatbots, RAG pipelines, vector databases, and distributed training or inference workloads. - Experience or background in HPC (High Performance Computing) environments for AI or ML applications. - Familiarity with multi-node GPU clusters and performance tuning for large-scale AI workloads. - Experience developing in cloud and/or virtualized environments, containerized solutions, with knowledge of Docker, Kubernetes - Background with common deep learning frameworks such as PyTorch or JAX. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been reinventing computer graphics, PC gaming, and accelerated computing for 30 years. It is a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, generative AI, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. We are seeking a highly skilled Principal Software Engineer to jo in our dynamic team. Our company is at the forefront of technological innovation, and we are dedicated to drivin g efficiency, defi ning platform architecture, and optimizing the performance of our infrastructure both on-prem and in the cloud. You will lead the architectural vision for a massive global platform and spearhead the operationalization of our internal frontier-class AI inference syste ms. Join us in this exciting endeavor! What You Will Be Doing: - Define Platform Architecture: Lead initiatives to architect and transform our global enterprise compute platform—running thousands of nodes and tens of thousands of VMs and containers via OpenShift and KubeVirt—by defining service tiers, SLAs, and automated cluster lifecycles. - Operationalize Frontier AI Infrastructure: Build the operational foundation for our internal AI inference platform scaling to frontier-class models. You will develop automated remediation pipelines, hardware watchdogs, and telemetry for pre-release, rack-scale GPU systems (including Blackwell and upcoming architectures). - Drive Strategic Capacity & Scale: Collect and review system data for capacity planning to navigate extreme hardware supply constraints. Develop proactive strategies, including public cloud bursting, hardware dogfooding, and evaluating alternative compute architectures (e.g., ARM). - Build the "Paved Road": Collaborate with highly autonomous NVIDIA engineering teams to drive cultural adoption of standard platforms. You will design compelling self-service architectures, APIs, and Terraform/OpenTofu providers that teams want to use. - Lead Complex Migrations: Evaluate existing application architectures and drive the fraught but critical migration of massive legacy workloads—including large-scale, long-running VDI environments—into modern Kubernetes orchestration. What We Need To See: - Bachelor’s degree in Engineering, Computer Science, Mathematics, or related field, or equivalent experience. - 15+ years of proven experience in compute platform engineering, site reliability, or systems architecture with a heavy focus on automation at massive scale. - Deep expertise in Kubernetes architecture and designing/deploying virtualization architectures, specifically operating VMs inside K8s (KubeVirt, OpenShift). - In-depth knowledge of hardware technologies (GPUs, high-speed backplane networking) with a track record of mitigating hardware-level failures, silent data corruption, and anomalies in large-scale environments. - Experience running large global environments spanning bare metal, virtualized infrastructure, and cloud with a unified GitOps posture (ArgoCD or similar). - Proficiency in programming languages such as Go and/or Python, alongside expert-level infrastructure-as-code development (Terraform, Config Management). - Strong leadership skills with the ability to influence technical direction across highly autonomous teams without relying on top-down mandates. Ways To Stand Out From The Crowd: - Hands-on experience managing bleeding-edge, pre-release hardware in production environments. - Deep understanding of advanced storage migrations and protocols (NFSv4, NVMe/TCP, Hyperconverged storage). - Solid understanding of microservices architecture and seamless multi-cloud deployment strategies (AWS, GCP). - Proven track record of building "Day 2" operational maturity (self-service, advanced auto-remediation, strict SLAs) from the ground up on existing foundations. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you are creative and autonomous, we want to hear from you! LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 391,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is seeking a motivated AI Model Development Researcher to join the TAO — Train, Adapt, Optimize — Multi-Modal Model Development team in Hanoi or Ho Chi Minh City, Vietnam. In this role, you will contribute to the development, adaptation, optimization, and evaluation of advanced AI models within the NVIDIA frameworks. You will work on cutting-edge areas such as multi-modal learning, vision-language models, image segmentation, foundation model adaptation, and scalable deep learning workflows. You will collaborate with engineers, researchers, and cross-functional teams to build practical AI solutions that can be integrated into production pipelines, NVIDIA SDKs, and real-world customer use cases. This is an excellent opportunity for an early-career engineer/scientist who is passionate about machine learning, deep learning, vision-language models, and building high-quality AI software. What you'll be doing: - Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. - Contributes to the design and implementation of vision-language models (VLMs) and universal segmentation systems. - Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. - Collaborate with cross-functional teams to integrate your research into production-level pipelines and NVIDIA SDKs. - Participate in research discussions, code reviews, and technical documentation to share insights and improve methodologies. What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or a related field (or equivalent experience). - 2+ years of experience in machine learning, deep learning, or computer vision model development. - Strong Python programming skills and proficiency with PyTorch or similar frameworks. - Solid understanding of neural network architectures, transformers, and multi-modal learning techniques. - Excellent problem-solving abilities, attention to detail, and a collaborative mindset. - Familiarity with vision-language models, image segmentation, or large-scale pretraining is a strong plus. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are now looking for a Senior Physical Design Engineer. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice to join our diverse team today. What you'll be doing: - Responsible for all aspects of physical design and implementation of GPU and other ASICs targeted at the desktop, laptop, workstation, and mobile markets. - As a member of a team, we will all participate in establishing physical design methodologies, flow automation, chip floorplan, power/clock distribution, chip assembly and P&R, timing closure. - Craft designs for static timing analysis, power and noise analysis and back-end verification. What we need to see: - BSEE (MSEE preferred) or equivalent experience. - 8+ years of experience in large VLSI physical design implementation on 5nm, 4nm and 3nm technology. - Your successful track record of delivering designs to production is a requirement. - Shown experience in the following areas: Power, Performance and Area improvement Initiatives is a plus. - Already a validated strong power user of P&R, Timing analysis, Physical Verification and IR Drop Analysis CAD tools from Synopsys (ICC2/DC/PT/STAR-RC/ICV),Cadence (Innovus, Tempus, SeaHawk ) and Mentor Graphics. - Deep understanding of custom macro blocks such as RAMs, CAMs, high-speed IO drivers, PLLs. - Confirmed prior experience in timing closure, clock/power distribution and analysis, RC extraction and correlation, place/ route and tapeout solutions. - To be successful you should possess strong analytical and debugging skills required. - Proficiency using Python, Perl, Tcl, Make scripting is helpful. NVIDIA is widely considered to be the leader of AI computing, and one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

At NVIDIA, our work powers accelerated computing and modern AI — from scientific research to the generative AI applications reshaping our world. The PCIe physical layer is where firmware meets the silicon: link bring-up, signal integrity, and cross-generation behavior on real silicon and in real customer environments. NVIDIA is building a dedicated Physical Layer team within its PCIe Firmware organization, with ownership across the networking product portfolio — and we are looking for a hands-on first-line manager to lead it! What you'll be doing: - Lead a focused team of physical layer firmware engineers as a player-coach — guiding debug directly while growing the team's engineers and tech leads. - Own the team's delivery for PCIe link bring-up, equalization, recovery, and physical-layer-related customer escalations across multiple products. - Partner with Chip Design, Architecture, Software, Validation, and Customer Engineering to drive issues to root cause and turn point fixes into reusable improvements. - Act as the technical reference on physical layer scope — both for triage and for cleanly identifying when an issue is not physical layer. - Champion AI-native engineering inside the team and across the organization, applying AI tools to triage, debug, and knowledge capture. What we need to see: - Degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. - 8+ overall years of engineering experience, with 3+ years in engineering management or equivalent tech lead experience on a path into management. - Strong PCIe foundation: link training, equalization, recovery flows, and cross-generation behavior. - A track record of personally driving hard link issues to root cause, working from state traces and eye diagrams alongside silicon and signal integrity engineers. - Proven ability to grow engineers, run a delivery cadence, and make prioritization calls under constraint. - An active operator: when execution is blocked, you step in. - Clear communicator across engineers, partners, and customers. Ways to stand out of the crowd: - Hands-on PCIe link bring-up on real silicon, signal integrity work, lane margining, or cross-generation interop. - Direct experience with high-speed SerDes behavior, thermal-sensitive link issues, or customer-facing escalation work. - Practical use of AI/ML tools in engineering — pattern matching across logs, summarizing state machine traces, building shared knowledge bases. - Familiarity with networking products, Linux, and scripting in Python. - Experience operating across HW/FW/SW boundaries. This is a chance to build and lead a new team with direct ownership of a critical technical surface across NVIDIA's networking portfolio. If that fits you — apply! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. We are committed to making reasonable accommodations for qualified individuals with disabilities. If you need assistance or accommodation during the application process, please contact us.

NVIDIA seeks a senior software engineer to join the AI Networking co-design and benchmark R&D team. In this pivotal role, the candidate is responsible for building and productizing machine learning tools. These include tools that use ML-based combinatorial optimization and build space exploration (DSE) techniques. These tools will be employed to optimize AI workloads across large GPU and CPU clusters, thereby ensuring the most efficient and productive utilization of system resources at data center scale. The role involves working on distributed Deep Learning, particularly within LLM training and inference stacks. A strong passion for collective communication and networking is desirable. The candidate will interact with diverse hardware and platforms, such as Host Channel Adapters (HCAs), Switches, CPUs, GPUs, and complete Systems. Furthermore, the role requires engagement across multiple software layers, including LLM applications, machine learning frameworks, and communication and computing libraries. The candidate will develop tools and methodologies using Machine Learning (ML) for comprehensive performance analysis and optimization, potentially incorporating learning-based agentic techniques. This work involves deep-diving across the software stack, from LLM applications and ML frameworks down to communication and computing libraries. This position offers a distinct opportunity to support the core infrastructure powering the next generation of large-scale AI systems. What you'll be doing: - Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization techniques) to optimize LLM models at datacenter scale. - Research, develop, and deploy AI/ML techniques to optimize large-scale Deep Learning (LLM) training and inference on NVIDIA supercomputers and distributed systems. This includes a focus on high-performance networking and NVIDIA communication libraries. - Build and productionize ML-based tools for performance prediction and optimization, with a strong emphasis on networking aspects. - Develop and deploy a scalable, reliable data curation pipeline capable of handling complex data types, such as time series and PyTorch model graphs, to effectively support the training of high-performance Machine Learning models. - Collaborate across hardware and software teams to deliver valuable performance analysis insights. - Lead performance test planning, establish performance targets for new technologies and solutions, and drive efforts to achieve those performance goals. What we need to see: - PhD or Master's degree in Computer Science, Software Engineering, or equivalent experience. - 4+ years of experience applying machine learning techniques to computer architecture and system optimization problems. Desired experience involves bringing to bear ML at the intersection of at least two of the following areas: HPC, networking, and AI applications. - Hands-on experience developing and deploying various learning algorithms (e.g., reinforcement learning, offline RL, supervised learning) to tackle optimization challenges within computer architecture, system design, or networking domains. - Proficiency in building and using ML models with leading frameworks such as PyTorch or TensorFlow, or JAX. - Proven ability to apply GNNs/transformers-based optimization to PyTorch model graph and Kineto execution traces. - Expertise combining knowledge of NVIDIA GPUs, the CUDA library, and deep learning frameworks (TensorFlow/PyTorch) with networking concepts, including collective communication libraries (like NCCL) and protocols (such as RoCE and RDMA). - Strong programming capabilities in Python, Bash, and C++. - A collaborative teammate with effective communication and interpersonal abilities. Ways to stand out from the crowd: - In-depth knowledge and experience with machine learning/reinforcement learning and frameworks. - Comprehensive understanding of computer architecture, system architecture and networking. - Extensive experience in applying machine learning techniques such as GNNs or related graph-based models. - Knowledge in PyTorch, CUDA, and NCCL libraries. - Proven software engineering/development skills With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we’d love to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. At NVIDIA, we’re building the future of autonomous driving — from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: Data. Extensive, diverse, high-quality data. We are seeking a  highly skilled Deep Learning Engineer to develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world’s most advanced AI platforms. We are looking for hands-on experience training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments. You will collaborate with other researchers, software engineers to bring pioneering AI models from prototype to production. What you will be doing: - Explore SOTA LLM/VLM models for search and classification of AV scenarios - Hands on model developments such as fine-tuning large LLM/VLMs for internal use cases - Collaborate with software engineers and researchers to ensure seamless integration of models from training to deployment. What we want to see: - Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience) - 10+ years of professional experience in deep learning or applied machine learning. - Strong foundation in deep learning algorithms, including hands-on experience with LLMs and VLMs - Deep understanding of general transformer architectures, inference bottlenecks, and popular model architectures such Qwen family. - Proficient in building and deploying models using PyTorch in production-grade environments. - Solid programming skills in Python Ways to stand out from the crowd: - Proven experience deploying LLMs or VLMs at scale in real-world applications using vLLM, SGLang. - Hands-on experience with SFT, DPO, GRPO techniques for fine-tuning - Proven experience in developing image and video search solutions at scale. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

The NVIDIA developer marketing group is looking for a developer advocate who is passionate about working with innovative technology, building well-documented inspirational demos, and sharing that code with the AI community. Our team is deeply committed to championing the developer ecosystem that builds applications on NVIDIA’s platform. We need a candidate who understands developers and works with the developer marketing on launching new technology. Do you have the rare blend of both engineering and marketing skills? We need hard-working and creative people who are passionate about teaching our developer community how to employ accelerated computing. If you aspire to this calling, we would love to learn more about you! What you'll be doing: - Create impactful and relevant content (e.g., demos, blogs, presentations, videos, etc.) and engage with developers, researchers, and students at events online or in person. - Collaborate with the product marketing team to launch emerging technology, write code, and share it with the community to inspire developers. - Actively participate on public-facing NVIDIA channels, including forums, Discord, and social media, helping developers understand our demos and encouraging them to build their own applications. - Some travel may be required to present at trade shows and conferences. What we need to see: - Bachelor's degree in Computer Science or related field (or equivalent experience). - 5+ years of relevant experience, including 3 years of engineering experience (or equivalent). - World-class communication and presentation skills with a proven track record of articulating the value proposition of an emerging technology. - Experience presenting to technical audiences and writing developer-facing content. You will be asked to provide samples of prior work. - Ability to design and implement Reinforcement learning and post-training pipelines for LLM to improve model reasoning, safety, and instruction-following capabilities. - Strong programming skills with the ability to develop easy-to-understand examples on training pipeline using AI frameworks such as PyTorch, JAX, and NeMo-RL - Ability to prioritize and work through constantly evolving projects that strive to demonstrate the benefits of new, potentially unstable technology. Ways to stand out from the crowd: - In-depth knowledge of software architecture, system design, and application development. - Hands-on experience popular reinforcement learning libraries such as Unsloth, TRL, OpenRLHF. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA's Silicon Co-Design Group (SCG) is seeking Senior AI Platform Engineers to set the technical direction and own end-to-end delivery of the AI-driven efficiency platform powering our intelligent automation ecosystem. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production — over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we need the engineer who defines the architecture everyone else builds on. In this role, you will set the platform strategy, own the full lifecycle of a production AI infrastructure, and drive alignment across multiple engineering departments — with personal accountability for its reliability, scalability, and long-term evolution. If you are energized by building foundational platforms at the intersection of ML infrastructure and large-scale systems, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed! What you'll be doing: - Leading technical strategy and roadmap for the AI-driven efficiency platform to meet SCG cross-functional use cases, investment areas and priority: defining architectural direction, making infrastructure investment decisions, and aligning roadmap priorities across silicon design, methodology, validation, and applied AI teams. - Partnering with domain agent builders across SCG teams and functional domains to define platform contracts and onboard new agents and skills. - Owning end-to-end delivery of the platform — from design and implementation through sustained production operation — with accountability for security, reliability, performance, and evolution. - Driving platform-wide decisions with cross-functional impact and leading the unified solutions: orchestration patterns, authentication and authorization, observability and SLA enforcement, and storage and caching strategies that scale across heterogeneous compute environments. - Serving as the technical authority for AI-driven infrastructure across SCG: setting engineering standards, resolving cross-team architectural conflicts, and mentoring senior engineers. - Identifying gaps and opportunities at the frontier of AI-driven infrastructure tooling — evaluating emerging technologies, shaping internal standards, and contributing learnings back to SCG engineering organization. What we need to see: - BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 12+ years of hands-on experience designing and operating production-grade platform or backend infrastructure. - 5+ years of direct ML infrastructure experience, including end-to-end ownership of a model serving platform or latency-sensitive backend service from initial architecture through sustained production operation. - Demonstrated track record of setting technical direction at the department or company level: defining platform strategy, establishing architectural standards, and leading initiatives spanning multiple teams. - Strong Python skills and proficiency in at least one compiled language such as C, C++, Go, Java, or Rust. - Hands-on experience with job queues + sandboxed execution (Kubernetes Jobs, Celery/Sidekiq/Temporal, container runtimes with resource isolation). - Proven ability to own high-stakes systems with rigorous operational discipline: structured observability, graceful degradation, clearly defined SLOs, and a sustained track record of reliability under pressure. - Strong communication and leadership skills, with the ability to align senior stakeholders and drive architectural decisions across organizations with competing priorities. Ways to stand out from the crowd: - Industry recognition in ML infrastructure or distributed systems — through publications, conference talks, open-source contributions, or technical leadership visible beyond your current organization. - Experience driving platform architecture at company scale, including engineering standards or frameworks broadly adopted by other teams. - Exposure to silicon design, methodology, validation or EDA toolchains, especially the cadence of chip development lifecycles. - Experience building or operating AI platforms within a silicon development, validation or EDA environment, with firsthand understanding of the reliability and scale demands of chip design toolchains. - Track record of mentoring senior engineers and growing technical talent — shaping the capabilities of the team as much as the platform itself. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family ( www.nvidiabenefits.com ).

Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence. They act as the brain of computers, robots, and self-driving cars. These machines can perceive and interpret their surroundings. We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value. What you'll be doing: - Develop and improve the technical build, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving. Use innovative CNN and transformer-based architectures when appropriate. - Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception. - Build efficient, production-grade deep learning models by defining objectives with the team. Select and prototype architectures, run experiments, and follow training and evaluation guidelines. Use techniques like large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA). - Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial. - Contribute to the data strategy for perception by specifying data and labeling requirements. Help prioritize data collection and annotation. Collaborate with data and ground-truth teams, including model-assisted workflows such as active learning, auto-labeling, and multimodal AI systems combining vision and language. Also work with model-in-the-loop tooling. - Collaborate with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale. What we need to see: - PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Proven experience in data-driven development, including close collaboration with data, labeling, and validation teams on data strategy, labeling quality, and iterative model improvement. - Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams. Ways to stand out from the crowd: - Experience designing and deploying perception solutions for autonomous driving or robotics using camera-based deep learning at scale. - Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms. This includes optimizing for latency, memory, and compute constraints. Experience with modern architectures such as CNNs and transformers is required. Familiarity with methods such as extensive pretraining, efficient tuning of parameters (e.g., LoRA), or vision-language models (VLMs) is also needed. - Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS). - Deep understanding of 3D computer vision fundamentals, including camera modeling and calibration (intrinsic and extrinsic), multi-view geometry, and 3D representations, ideally with experience applying these concepts in transformer-based 3D or BEV perception pipelines. - Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components.

Do you want to help drive the development of CPU technology for architectures used for artificial intelligence (AI), agentic workloads, deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and autonomous vehicles? Come join the CPU architecture team and help us the boundaries for all our CPU products! What you'll be doing: - Bridge the gap between architecture, RTL implementation, and physical design. - Serve as subject matter expert on power delivery/regulators, power gating, di/dt, and thermal throttling. - Analyze power trade-offs for different die stacking and packaging proposals. - Propose and drive improvements related to power and power methodology for our custom CPU cores. What we need to see: - BS/MS in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. - 15 or more years of relevant experience. - Extensive background in CPU architecture. - Solid understanding of power consumption, and power efficiency concepts. - Experience of RTL development. - Detailed understanding of process technologies and circuit design. - Well versed in low power techniques that span the entire stack from SW, Architecture, RTL, VLSI, and process. Ways to stand out from the crowd: - PhD or research experience. - Advanced knowledge in the area of physical design. - Knowledge of GPU and SOC design. - Experience of advanced packaging technologies. - Strong communication skills. NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries — from robotics and autonomous vehicles to healthcare and climate research. With the introduction of the Grace CPU Superchip, and more recently, the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA’s broader technology stack, enabling faster AI model training, agentic use-cases, efficient data processing, and scalable cloud deployments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking an AI Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate brings broad experience across machine learning, including reinforcement learning, genetic/evolutionary algorithms, predictive modeling, complex systems, and high-dimensional data analysis, along with strong foundations in compiler design and domain-specific languages. This role is focused on building AI-driven compiler intelligence for production compiler pipelines, delivering measurable improvements in performance and efficiency, and advancing LLM-enabled workflows for compiler decisioning and developer productivity. What you'll be doing: - Join a team driving innovative solutions in compilers and developer tools through applied machine learning and AI. - Collaborate with world-class engineers to shape next-generation compiler capabilities that power large-scale, high-impact products. - Design and implement end-to-end compiler optimization workflows, from feature engineering and model development to compiler integration and production rollout. - Develop and integrate learning-based decision systems into compiler passes, code generation flows, and optimization pipelines. - Build robust interfaces between LLM systems and compiler infrastructure for optimization recommendations, decision support, and workflow automation. - Partner with compiler, architecture, and performance teams to validate impact on representative workloads and benchmark suites. - Lead experimentation, evaluation, and deployment with strong standards for reliability, scalability, and performance. What we need to see: - BS/MS/PhD in Computer Science or a related field (or equivalent experience), with a focus on machine learning and compiler/developer tools. - 8+ years of software engineering and AI/ML experience, preferably in tools or systems development. - Strong knowledge of compilers, code generation, and GPU architecture. - Demonstrated proficiency in Python and C/C++. - Strong mathematical and scientific foundation relevant to AI/ML and compiler technologies. - Hands-on experience with LLVM/MLIR-based compiler development, including optimization passes, code generation, or frontend integration. - Experience building or integrating LLM-based systems, agents, or developer tooling in production environments. Ways to Stand Out From the Crowd - Deep familiarity with reinforcement learning, genetic/evolutionary algorithms, predictive modeling, and complex systems. - Proven track record of deploying AI/ML solutions in production and embedded environments. - Strong experience integrating LLMs into systems workflows with attention to reliability, latency, and evaluation quality. - Demonstrated measurable outcomes such as runtime gains, compile-time improvements, or efficiency improvements on real-world workloads. - Publications, open-source contributions, or patents in compilers, AI/ML systems, or performance engineering. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous program manager with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearning

NVIDIA is looking for a Data Center Network Deployment Engineer to join the Networking clusters solutions HPC/AI Infrastructure team. We are building supercomputers and AI clusters based on groundbreaking technologies. We are looking for a network/system engineer to be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing. You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. Does this sound like you? If so, we would love to hear from you! What you'll be doing: - Deploy, manage and maintain large scale AI Data Centers  - control, network and storage stack - Work with multiple software and hardware teams to optimize the clusters networking health and performance - Develop and implement automation scripts for network, compute and storage operations and deployments - Supporting Research & Development activities and engaging in POCs/POVs for future improvements What we need to see: - B.Sc. in Engineering or CCNP certificate - 8+ years of proficiency in networking fundamentals, configuring ethernet switches, understanding the TCP/IP stack, and data center architecture. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalls, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Proactive individual with the ability to work independently, prioritizing tasks to optimize technology and enhance customer experience. - Provides ad-hoc knowledge transfers, develops handover materials, and offers deployment support for engagements. Ways to stand out from the crowd: - Combination of interpersonal skills and technical competence - Knowledge of HPC and AI solution technologies from CPUs and GPUs to high speed interconnects and supporting software - Experience with multiple storage solutions such as Lustre, GPFS, and newer and emerging storage technologies. - Automation tooling background (Ansible, Salt, Puppet etc.). NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you! LI-Hybrid

NVIDIA is looking for an experienced HPC DevOps and Network Engineer to help us build the supercomputers and HPC clusters of the future. As a Senior HPC DevOps Engineer, you'll be a key player in groundbreaking advancements in artificial intelligence and GPU computing. Your expertise will drive the latest breakthroughs, providing insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. What you’ll be doing: - Innovate and Implement: Design, implement, and maintain large-scale HPC/AI clusters with state-of-the-art monitoring, logging, and alerting systems. - Infrastructure as Code (IaC): Utilize and develop tools to manage infrastructure as code, ensuring scalable and repeatable deployments. - Streamline CI/CD Pipelines: Develop and maintain continuous integration and continuous delivery (CI/CD) pipelines to automate and streamline deployment processes. - Automate Everything: Develop automation scripts and tools to automate deployment, configuration management, and operational monitoring. - Develop complex Networking automations. - Troubleshoot Complex Issues: Perform comprehensive troubleshooting from bare metal to application level, ensuring system reliability and efficiency. - Lead and Educate: Serve as a technical resource, developing and sharing best practices with internal teams. - Drive Innovation: Support R&D activities and engage in proof of concepts (POCs) and proof of values (POVs) for future improvements. What we need to see: - B.Sc. in Computer Science, Engineering, or a related field with 5+ years of experience. - Deep knowledge of HPC and AI solution technologies, including CPUs, GPUs, high-speed interconnects, and supporting software. - Advanced proficiency in programming and scripting languages, with a solid understanding of object-oriented programming principles. - Familiarity with Jenkins, Ansible, Puppet/Chef. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu), networking and OS-level security. - Deep understanding of networking protocols such as InfiniBand and Ethernet. - Experience with job scheduling workloads and orchestration tools such as Slurm and Kubernetes. - Experience with multiple storage solutions like Lustre, GPFS, ZFS, and XFS. - Expertise with virtual systems (VMware, Hyper-V, KVM, Citrix). - Familiarity with cloud platforms (AWS, Azure, Google Cloud). Ways to stand out from the crowd: - Proven networking experience or strong knowledge through professional networking training. - Architectural Insight: Knowledge of CPU and/or GPU architecture. - Container Expertise: Understanding of Kubernetes and container-related microservice technologies. - GPU Focus: Experience with GPU-focused hardware/software (DGX, CUDA). - RDMA Fabrics: Background with RDMA (InfiniBand or RoCE) fabrics. At NVIDIA, we value diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We provide reasonable accommodations to ensure all individuals can participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Join us and be part of a team that's pushing the boundaries of technology and making a real impact in the world.

Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production. Over 200 product SKUs were optimized during the Blackwell generation alone! Now we're looking for an engineer to help us rebuild that toolchain around AI. We focus on the silicon layer of NVIDIA's productization work: the chip behavior piece. Our tools run the simulation, configuration, and data flow that take a chip's power, performance, and yield from pre-silicon estimates through to the values that ship in firmware and populate customer specs. This role is about making those tools talk to each other better, using AI to optimally move outputs from simulation into the downstream firmware, manufacturing, and specification systems that consume them. What you'll be doing: - Build the infrastructure that turns raw simulation data (power, noise, binning yields, and more) into real firmware tuning, product specs, and manufacturing limits. You own the pipelines between tools. - Use LLMs and agents across the toolchain to automate the analysis, validation, and reporting work that currently costs engineering countless hours per chip. - Build the observability and validation systems that catch data errors and inconsistencies before they turn into release blockers. - Work with product convergence, silicon architecture, firmware, and manufacturing teams to translate new hardware requirements and capabilities into workflows that make it to production. What we need to see: - BS/MS in CS, CE, EE, or Systems Engineering, or equivalent experience. - 4+ years shipping production Python services and data pipelines (FastAPI, async workflows, databases, modern web frontends). - Hands-on experience applying LLMs to engineering problems: agents, MCP, RAG, or evaluation pipelines. Have shipped an LLM-backed feature in production and can tell us about a time you had to debug one. - Strong instincts for data quality: the automated checks, schema validation, and integration tests that keep pipelines trustworthy when inputs change. - You keep up with a fast-paced AI landscape and can distinguish which new tools matter and which are just hype Ways to stand out from the crowd: - Silicon product proficiency (speed, power, voltage noise, binning); MCP, DSPy, or LLM evaluation frameworks; Perl interop for legacy chip-data workflows; have crafted dashboards and visualizations for diverse collaborators. Keeping up with every new feature and architectural change that NVIDIA packs into each chip generation is a real challenge. And because our users are directly on the path to production, support questions don't always wait for business hours. The payoff is that every product NVIDIA ships goes through the systems you'll help build. If that's the kind of problem you want to work on, we'd like to talk.

Are you seeking an outstanding opportunity? We are looking for a Senior Photonic Layout Design Engineer – someone who is excited to join a growing group of diverse individuals responsible for handling high-speed mixed-signal & Silicon Photonic Designs! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Join our diverse team today! What You'll Be Doing: - As a Senior Photonics Layout Engineer, you will take ownership of the physical design and verification of cutting-edge photonic integrated circuits (PICs), guiding designs from initial proof-of-concept phases to high-volume manufacturing readiness. You will work within a highly collaborative, multidisciplinary team of photonics, CMOS, packaging, and systems engineers to drive next-generation Silicon Photonics (SiPh) and SERDES products. - Layout Execution & Tape-out Ownership: Lead complex, full-loop manual and automated layout designs for waveguides, modulators, photodetectors, and mixed-signal functions (high-speed/general I/Os, ESD structures). Drive the full tape-out process, including floor planning, waveguide routing, and mask data preparation. - Verification & Mitigation: Execute rigorous post-layout verification (DRC, LVS, fill, density) across multiple stepping versions. Trace defect sources, mitigate layout-dependent issues, and ensure DRC/LVS cleanliness prior to tape-out. - Test Vehicle & Component Development: Own the layout of complex test structures, active/passive full loops, and certification vehicles with large Design of Experiments (DOEs) to optimize for process windows. - Automation & AI-Assisted Workflows: Develop and implement AI-assisted design methods, layout automation scripts, and custom Pcells to improve productivity, reduce development cycle times, and customize DRC/LVS checking flows. What We Need to See: - To succeed in this role, candidates must possess a deep technical understanding of advanced node semiconductor fabrication, sophisticated automation capabilities, and a proven track record of first-time success on high-density chip designs. - BS, MS, or Ph.D. in Electrical Engineering, Physics, or a closely related field (or equivalent experience). At least 6+ years of hands-on, full-chip layout design experience in semiconductor, analog, or silicon photonics industries. - Deep understanding of analog circuit layout, Silicon Photonic constraints, and device physics within advanced sub-micron CMOS and SiPh technologies. - Proven expertise with Cadence Virtuoso (Custom Layout, SDL) and industry-standard verification suites (Calibre, Hercules, ICV, Dracula, or Primeyield). - Strong proficiency in programming and scripting languages (Python, SKILL, Perl, TCL, or C++) for layout automation, file I/O, data processing, and tape-out flows. - Ability to optimize workflows using best-known methods (BKMs), and proactively collaborate with integration, and design rule teams to achieve high-yield manufacturing goals. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD for Level 4, and 148,000 USD - 235,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA's success builds on a foundation of industry leading hardware. We achieve distinction through extensive design optimization, including combining the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and specialized algorithms for VLSI design. We are seeking a Senior P&R Methodology Architect to define and own the next generation RTL2GDS flow for advanced nodes (3nm and below) and high performance GPU, CPU and SoC designs. You should have deep, hands‑on experience across the full RTL2GDS flow, with expertise in key stages such as RTL, DFT, synthesis, placement, optimization, CTS, routing, and signoff. Creativity and self-drive to explore is required. Our engineers enjoy unusually high intellectual freedom and the ability to explore broad roles. If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, it does not get any better than this! What you’ll be doing: - Working directly with core P&R engine developers to define real‑world optimization problems, shape requirements and roadmaps, and provide detailed feedback on engine behavior, QoR, and scalability. - Defining and rolling out next‑gen flows, including refactoring legacy flows and consolidating ad‑hoc solutions into scalable, maintainable frameworks used across multiple design teams. - Designing and running rigorous A/B and multi‑variant experiments to compare flows, engines, and tool settings. Developing Python‑based analytics and ML/GenAI techniques to mine large QoR datasets, recommend flow settings, and automate analysis. - Performing deep root‑cause analysis on QoR issues across engines, tools, and flows, and driving methodologies to resolve the ‘long tail’ of timing closure and performance limiters. - Partnering with architecture, RTL, DFT, synthesis, physical design, power, signoff, and CAD/methodology teams as a key technical leader and bridge. - Driving aggressive PPA and schedule targets and the adoption of new tools and flows across the company. What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience. - 8+ years physical design experience, with deep expertise in industry standard tools like ICC2/Innovus, PrimeTime/Tempus, etc. - Extensive hands‑on P&R experience taking complex blocks or chips to tape‑out with aggressive PPA targets. - Proven skills in Python, Perl, and TCL flow development. - Strong problem‑solving skills and self‑motivation, demonstrated by simplifying complex, cluttered environments and modernizing legacy tools and processes. - Excellent communication and collaboration skills, with a track record of driving consensus and solving complex issues across distributed design, CAD, and R&D teams. Ways to stand out from the crowd: - Experience collaborating with EDA or internal R&D teams on core engine development, co‑defining features, developing benchmarks and leading validation and deployment. - Expertise in designing and automating A/B tests and large‑scale regressions, and analyzing large QoR datasets to understand trends and drive root‑cause analysis. - Background in advanced‑node and large‑scale designs with exposure to advanced‑node challenges (DFM, variability, EM/IR, power integrity). - Hands‑on experience applying AI/ML or GenAI to physical design, QoR analysis, or flow development will be a strong plus. If working hands‑on from early architecture and RTL through silicon, and serving as the connector between core developers, methodology teams, and users, excites you, we want to hear from you. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

An applied research team within NVIDIA’s Networking Systems & Software Architecture group is solving some of AI’s hardest infrastructure problems. The team builds systems-level software that moves data between GPUs, nodes, and storage at the speed modern AI demands—spanning low-level transport optimization, hardware-software co-design, and communication frameworks that plug directly into production AI stacks. The team's charter expands into emerging domains including quantum computing interconnects. The Senior Architect role is to own modules and projects end-to-end—from scoping research questions to shipping production code. It calls for a recognized expert who drives technical decisions, pulls in ideas from research and industry, and regularly prototypes new approaches to prove a point. The work lives at the boundary of applied research and production engineering! What you will be doing: - Architecting and implementing high-performance communication and memory management libraries for distributed AI - Driving hardware-software co-optimization with GPU, DPU, NIC, and switch teams through GPUDirect RDMA, NVLink, and next-generation interconnects - Profiling and optimizing data movement across GPU memory, system DRAM, NVMe, and network fabrics - Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM - Contributing to and maintaining open-source projects, mentoring engineers, conducting design reviews, and prototyping experimental technologies to evaluate their viability What we need to see: - 12+ years in systems software and/or networking with demonstrated ownership of complex projects. - MS, PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field. - Solid understanding of high-performance networking: InfiniBand, RoCE, RDMA, NVLink, GPUDirect. - Strong C/C++/Rust systems programming with comfort in performance profiling and low-level debugging. - Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns. Ways to stand out from the crowd: - Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. - Knowledge of storage networking (NVMe-oF, GPUDirect Storage, S3). - Background of Reinforcement Learning systems. With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we’d love to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for an Implementation Methodology Engineer to join NVIDIA VLSI team. If you are looking for a challenging and exciting role and you are a self-starter and highly motivated individual who loves to collaborate and find solutions to hard technical problems, join us today! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to pursue, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. What you’ll be doing: - You will be responsible for all aspects of front-end design implementation methodologies (synthesis, formal-equivalence-checking), flow automation and application support. - Use NVIDIA implementation flows and EDA tool expertise to improve power, performance and area on NVIDIA's most critical designs - You will collaborate with logic designers, physical designers and EDA vendors to solve exciting implementation issues and develop new solutions. - Provide support for EDA tools and flows What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, or related fields (or equivalent experience). - 4+ years of experience in logic design implementation and/or physical design implementation - Deep understanding of logic optimization techniques and relative area, timing, and power trade-offs - Strong understanding of physical design implementation eg: physical synthesis, placement, routing, logic restructuring, etc. - Should be a power user of synthesis and/or place and route EDA tools from Synopsys (DC/FC), Cadence (Genus/Innovus) - Good debugging and problem-solving skills - Strong interpersonal skills along with the ability to work in a dynamic team Ways to stand out from the crowd : - Prior experience in physical implementation - Proficiency in Python, Tcl, Make scripting NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of constant innovation and creating the highest performance products in the industry? If so, we want to hear from you. Come, join NVIDIA VLSI team and help build the real-time, cost-effective computing platform driving our success across multiple fields such as Deep Learning and AI, Robotics and Autonomous Driving, Gaming and High Performance Computing. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a candidate who is interested in driving the growth of NVIDIA GeForce RTX AI & Creator platform to consumers through engagement with developers. To stand out, demonstrate your sharp understanding on AI ecosystem in China and strong experience on consumer marketing. China is a dynamic and diverse developer communities, with distinct platforms, fast-evolving user behavior, strong local ecosystems, and highly engaged creator networks. This role is critical in helping build meaningful connections with developers and creators across China, while driving the adoption and market relevance of new AI and creator products through localized programs, strong community relationships, and impactful go-to-market execution. An ideal candidate possesses a strong passion for AI evolvement with new graphic technology, a deep understanding of global & China AI trend, a sharp marketing sense and a proven track record of driving successful marketing campaigns. You should be a creative thinker with exceptional communication skills and the ability to collaborate effectively with cross-functional teams. What you’ll be doing: - Identify, develop, and manage co-marketing opportunities with strategic partners, platforms, communities, and creators to expand reach and deepen ecosystem collaboration. - Design and execute localized developer marketing programs that engage technical audiences and creator communities through online and offline channels. - Drive go-to-market planning and execution for new AI and creator products, including launch messaging, content strategy, campaign programs, and community activation. - Partner closely with product, partnerships, developer relations, and regional or global marketing teams to align business goals with local market needs and audience insights. - Create compelling and locally relevant content such as campaign narratives, product launch materials, case studies, community stories, event content, and educational assets for developers and creators. - Gather insights and feedback from developers, creators, and partners in China, then translate those learnings into actionable recommendations for product positioning, messaging, and program improvement. - Support the growth of developer and creator communities by building engagement frameworks, nurturing key relationships, and encouraging ongoing participation in programs, events, and product initiatives. - Track program performance and market response, using data and qualitative feedback to optimize campaign effectiveness, audience engagement, and conversion outcomes over time. What we need to see: - Bachelor’s degree in marketing, business, and/or computer science; AI-related background is a plus. - 5+ years of experience in consumer marketing; AI, creator, PC, or consumer tech industries preferred. - Familiarity with China marketing AI ecosystem, coupled with a solid understanding of graphics technology. - Project management experience with excellent communication, prioritization, listening, collaboration, and organizational skills. - Strong understanding of marketing principles and channels, with pride in delivering excellent work and the ability to multitask. - Daring, driven, proactive, and adaptable, with a can-do attitude and strong attention to detail. - Ability to work well within a team, with self-discipline, flexibility, and accountability to complete tasks effectively. - Passion for learning, innovation, and continuously building marketing knowledge. Ways to stand out from the crowd: - Experience at developer marketing, especially AI or PC industry oriented. - Understands how to engage with young consumers on social media. - Sharp sense on marketing with creativity. - Understanding of AI, creator will be a good plus NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you. LI-Hybrid

A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and SW/HW teams running AI workload in GPU cluster. As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the performance and efficiency of the system. What you’ll be doing: - Build internal profiling and analysis tools for AI workloads at large scale - Build debugging tools for common encountered problems like memory or networking - Create benchmarking and simulation technologies for AI system or GPU cluster - Partner with HW architects to propose new features or improve existing features with real world use cases What we need to see: - BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development - Strong software skills in design, coding (C++ and Python), analytical, and debugging - Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference. - Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking - Experience with NVIDIA GPUs, CUDA Programming and NCCL - Motivated self-starter with strong problem-solving skills and customer-facing communication skills - Passion for continuous learning. Ability to work concurrently with multiple global groups Ways to stand out from the crowd: - Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms - Solid experience in large AI job performance analysis for training/inference workload - Knowledge of Linux device drivers and/or compiler implementation - Knowledge of GPU and/or CPU architecture and general computer architecture principles

NVIDIA AI Technology Center is seeking outstanding Senior Solutions Architects to catalyze the global research community by embedding NVIDIA as a core scientific collaborator. We move beyond standard technical support to act as elite research partners, driving the adoption of NVIDIA's platform through high-impact, co-authored breakthroughs and the shared pursuit of frontier AI discoveries. Primary focus on building foundation model engagements with researchers and developers at our key partner researcher from universities and joint labs. You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts dedicated to frontier model development. This role is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA! What you will be doing: - Create fruitful technical engagements with top developers and influential researchers from the universities or enterprises building foundation models in Korea and lead strategic relationships with them. - Help them develop AI models more efficiently by proposing state-of-the-art training and optimization frameworks including Megatron-LM, Megatron-Bridge, NeMo-RL, or TensorRT-LLM. - Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC. - Advise on the transition from experimental code to large-scale, production-ready research environments, demonstrating the performance leap provided by the NVIDIA technology stack. What we need to see: - PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - Proven experience in managing complex technical projects and navigating corporate strategic goals - 5+ year hands-on experience in full AI model lifecycle, including pre-training, supervised fine-tuning, post-training such as reinforcement learning, optimization, and evaluation. - Experience with NVIDIA GPUs and software libraries - Strong problem-solving and debugging skills - Excellent presentation, communication, and collaboration skills - Strong written and oral communication skills in English. Ways to stand out from the crowd: - Good track record of academic research publications - Experience working across academia, industry and the government - Understanding of infrastructure factors that can affect AI model development such as GPU architecture, server block diagram, or networking bandwidth among GPU servers or between GPU servers and shared storage. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you! NVIDIA is committed to encouraging a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA AI Technology Center is seeking outstanding Senior Solutions Architects to catalyze the global research community by embedding NVIDIA as a core scientific collaborator. We move beyond standard technical support to act as elite research partners, driving the adoption of NVIDIA's platform through high-impact, co-authored breakthroughs and the shared pursuit of frontier AI discoveries. Primary focus on scientific application engagements with researchers and developers at our key partner researcher from universities and joint labs. You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts dedicated to HPC applications. This role is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA! What you will be doing: - Analyze key scientific applications of top researchers from the universities or enterprises in Korea, understanding data type, input and output, workflow, runtime between CPU and GPU, proportion of MPI communications, etc. - Help them accelerate their applications by resolving the bottleneck that can be improved in latency or runtime perspectives using NVIDIA CUDA libraries and SDKs. - Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC. - Advise on the transition from experimental code to large-scale, production-ready research environments, demonstrating the performance leap provided by the NVIDIA technology stack. What we need to see: - PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - Proven experience in managing complex technical projects and navigating corporate strategic goals - 5+ year hands-on experience in one or two of HPC fields, for example, electronic structure calculations, molecular dynamics, computational fluid dynamics, astrophysics, numerical weather prediction, or quantum computing - Experience with NVIDIA GPUs and software libraries - Strong problem-solving and debugging skills - Excellent presentation, communication, and collaboration skills - Strong written and oral communication skills in English. Ways to stand out from the crowd: - Good track record of academic research publications - Experience working across academia, industry and the government - Experience with AI physics models and model architecture including developing, defining, training, and deploying open or proprietary models. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you! NVIDIA is committed to encouraging a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is looking for Senior Networking Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing - Primary responsibilities will include building AI/HPC infrastructure for new and existing customers. - Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting. - Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement. - Maintain services once they are live by measuring and monitoring availability, latency, and overall system health. - Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements. What We Need To See - BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields. - At least 5+ years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture - Proficiency in configuring, testing, validating, and resolving issues in LAN networks, especially in medium to large-scale HPC/AI environments. - Advanced knowledge of EVPN, BGP, OSPF, VXLAN protocols. - Hands-on experience with network switch/router platforms like Cumulus Linux, SONiC, IOS, JunosOS, and EOS. - Extensive experience delivering automated network provisioning solutions using tools like Ansible, Salt, and Python. - Ability to develop CI/CD pipelines for network operations. - Strong focus on customer needs and satisfaction. - Self-motivated with leadership skills to work collaboratively with customers and internal teams. - Strong written, verbal, and listening skills in English are essential. Ways To Stand Out From The Crowd - Familiarity with cloud networks (AWS, GCP, Azure) is a plus. - Linux or Networking Certifications. - Experience with High-performance computing architectures. Understanding of how job schedulers (Slurm, PBS) work. - Cluster management technologies knowledge (bonus credit for BCM (Base Command Manager).) - Experience with GPU (Graphics Processing Unit) focused hardware/software.

NVIDIA is looking for a Data Center Deployment Specialist to join its Professional Services team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest data centers in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. As a Data Center Infrastructure Specialist, you will be interacting with customers, partners, and internal teams, to analyze, define and implement large scale Datacenter projects. The scope of these efforts includes a combination of Datacenter Infrastructure design and cluster deployment planning. What you will be doing: - Design and implement flawless data center infrastructure solutions to meet the needs of our customers. - Collaborate with cross-functional teams to ensure the successful deployment of data center infrastructure. - Datacenter Planning: Floor Plan, Rack Elevation, Simulation - Cable deployment planning including - ensuring requirements are accurate such as number and type of connections, port assignments, and timing of activity while following standard methodologies, Point-to-Point Design. - Deploy and Support NVIDIA products. - Validating and updating all related work instructions for Datacenter activities. - Responsible for providing input for Data Center Standards updates as required; balancing multiple activities and priorities; participate in projects calls. - Documenting processes and keeping event logs What we need to see: - 3+ years of proven experience as a data center infrastructure engineer, field service engineer or similar with background in designing and implementing data center infrastructures. - Bachelor's degree or equivalent experience in a relevant field. - In-depth knowledge of data center environments, servers, and network equipment. - Extensive experience in installing, monitoring, and maintaining data center equipment. - Solid understanding of networking, storage, and virtualization technologies. - Excellent problem-solving skills and attention to detail. - Ability to work as part of a team, in a fast and highly dynamic environment. - Exceptional communication and interpersonal skills. - Proficiency in documenting processes. - Willingness to travel, around 30% Way to stand out from the crowd: - Network certification such as: Cisco Certified Network Associate (CCNA), Juniper Networks Certified Associate - Junos (JNCIA-Junos) - Knowledge with InfiniBand Technology - Collaboration with R&D and network engineering teams. - Excellent interpersonal communication and on-site coordination skills. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world, working for us. Our commitment to pushing boundaries and delivering exceptional solutions is unparalleled. As a Data Center Infrastructure Specialist, you will play a key role in shaping the future of computing and driving the success of our clients. At NVIDIA, we are an equal opportunity employer. We value diversity and are committed to creating an inclusive and supportive work environment for all employees. If you are a proactive and driven individual, creative with a strong interest in current technology trends, this is the opportunity you have been waiting for. Join us at NVIDIA and be part of our journey to shape the future of computing. Apply now and let's work together to make a difference!

NVIDIA Networking Product Security team is seeking an outstanding technical AI Security Architect with hands-on experience in secure software development lifecycle (SDLC) practices, AI-assisted engineering workflows, and agentic development environments. In this role, you will help define and transform how NVIDIA Networking teams build secure AI products by designing and deploying next-generation development methodologies powered by AI agents and intelligent automation. You will drive the integration of secure agentic development environments into the SDLC, enabling developers and security teams to build, validate, and secure AI products more efficiently and at scale. The ideal candidate combines deep security expertise with practical software development experience and a strong understanding of how AI-assisted development environments can reshape modern engineering practices. What you’ll be doing: - Define and evolve secure SDLC methodologies for NVIDIA Networking AI products using AI-assisted and agentic development environments. - Design frameworks and best practices for the secure adoption of AI coding assistants, autonomous agents, and AI-driven engineering workflows. - Architect secure agentic development environments that improve developer productivity while maintaining strong security controls and governance. - Partner with architecture, infrastructure, security, and R&D teams to integrate AI-native workflows into the software development lifecycle. - Define security guardrails, validation mechanisms, and policy enforcement for AI-assisted software development processes. - Design and recommend security architectures and controls to satisfy internal and external security requirements. - Lead initiatives that modernize secure engineering practices across large-scale development organizations. - Mentor developers, architects, and security engineers on secure AI development methodologies and best practices. What we need to see: - Academic degree in Computer Science, Electrical Engineering, Cybersecurity, or related field. Equivalent experience will also be considered. - 5+ years of experience in security engineering, application security, or security architecture. - Strong understanding of modern SDLC processes, developer workflows, and secure software engineering practices. - Hands-on experience designing, building, or operating agentic development environments or AI-assisted engineering platforms. - Experience securing AI applications and integrating AI tools into enterprise development workflows. - Familiarity with AI coding assistants, autonomous agents, LLM frameworks, and orchestration systems. - Experience defining security policies and governance for AI-enabled development environments. - Ability to drive significant organizational and engineering process changes across large-scale teams. - Ability to work independently and collaboratively in a constantly evolving environment. - Excellent communication and interpersonal skills. Ways to stand out from the crowd: - Experience building AI-native developer platforms or internal engineering productivity systems. - Experience managing or influencing large R&D organizations and engineering transformation initiatives. - Familiarity with cloud-native security, Kubernetes, and large-scale distributed systems. - Experience designing governance frameworks for enterprise AI adoption. - Demonstrated thought leadership through publications, conference talks, or open-source contributions related to AI security or developer tooling. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us and, due to unprecedented growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We don't just build the hardware and software that powers the AI revolution — we are building the AI that designs the next generation of both. Our team sits at the intersection of inference software and GPU architecture, creating autonomous LLM-driven systems that reason about hardware, write high-performance CUDA, and automate the complex loops of architectural simulation, analysis, and optimization. We are looking for a senior LLM Agents Architect to work hands-on with hardware architects, verification engineers, GPU performance experts, and software developers to build end-to-end agent flows that drive significant improvements in kernel optimization, architectural exploration, and developer efficiency. What you'll be doing: - Design and build agentic AI systems that generate, analyze, and optimize GPU compute kernels — targeting speed-of-light performance on NVIDIA hardware. - Collaborate with GPU architects and performance engineers to encode domain expertise — memory hierarchy trade-offs, occupancy tuning, instruction-level reasoning — into agent workflows that rival hand-tuned optimization. - Build automated performance forensics agents capable of ingesting large-scale simulation traces and Nsight profiler data to identify bottlenecks and propose architectural or software mitigations. - Partner with HW architects to develop agentic flows for GPU architectural studies — enabling rapid what-if analysis across micro-architecture configurations such as cache sizing, memory controller design, and compute unit scaling. - Explore agentic approaches to HW/SW co-design challenges, including replacing or augmenting graph-compiler functionality (e.g., TorchInductor) with LLM-driven optimization and code-generation pipelines. - Rapidly prototype and thoughtfully productize; integrate with internal services, utilize GPU capabilities, remove bottlenecks, and deliver fitting solutions. - Set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements. - Mentor and improve teams through insights in agent orchestration, prompting, RAG, observability, crafting documentation and playbooks for NVIDIA's teams. What we need to see: - 8+ years in applied ML/AI or large-scale systems, with 2+ years crafting agentic or LLM-powered applications in production environments. - B.Sc in Computer Science / Electrical Engineering. - Solid grounding in computer architecture: memory hierarchies, parallelism models, pipelining, and cache behavior. Specific familiarity with NVIDIA GPU architecture — streaming multiprocessors, warp scheduling, shared/global memory model, and occupancy reasoning — is essential. - Hands-on CUDA programming experience: writing, profiling, and optimizing GPU kernels — not just calling into CUDA-accelerated libraries. Comfortable with tools such as Nsight Compute, Nsight Systems, or equivalent profiling workflows. - Proven ownership of at least one end-to-end agentic system or LLM application: requirements, architecture, implementation, evaluation, and incremental hardening in production — not just experience with off-the-shelf frameworks. - Strong software engineering skills in Python and one systems language (C++ preferred). - Proficient in tool use, RAG pipelines, and model adaptation techniques for building agentic systems. - Demonstrated ability to collaborate with HW/SW domain experts and translate their heuristics into deterministic tools, constraints, and evaluation metrics. - Excellence in communication and facilitation: aligning diverse collaborators, documenting decisions/assumptions, and influencing without authority. - Track record of building observability for AI systems: dataset/version management, offline test suites, online telemetry, guardrails/safety checks, and rollback plans. Ways to stand out from the crowd: - Familiarity with the PyTorch compilation and lowering stack (torch.compile, TorchDynamo, TorchInductor, Triton, down to PTX), and with GPU graph compilers, kernel fusion strategies, or auto-tuning frameworks. - Background in performance engineering for HPC or GPU-accelerated workloads, including experience with performance modeling or hardware simulators. - Familiarity with distributed processing, multi-GPU workloads, and networking (e.g., NVLink, InfiniBand). - Familiarity with frontier agentic coding tools (e.g., Claude Code, Codex, Cursor) — understanding their underlying architecture: tool orchestration, context management, and autonomous task execution patterns. - Hands-on experience building a domain-specific coding agent — whether on top of frontier agentic harnesses (e.g., Claude Code, Codex SDK) or lower-level agent frameworks (e.g., LangChain/LangGraph deep agents, CrewAI). Comfortable with the design choices that make a coding agent useful in practice: task scoping, tool and context curation, evaluation, and failure recovery Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale. The ideal candidate brings deep technical credibility in foundational AI, strong research engagement experience, and hands-on expertise in either AI inference research or AI training research. What you'll be doing: - Serve as a trusted technical advisor to leading academic AI labs working on foundation models, LLMs, multimodal AI, reasoning, training, inference, and AI systems. - Identify high-impact research workloads where NVIDIA software, systems, and accelerated computing platforms can advance model performance, scale, and efficiency. - Engage principal investigators, postdocs, graduate researchers, and lab leadership to understand research goals, technical blockers, infrastructure needs, and collaboration opportunities. - Track frontier AI research across papers, benchmarks, open-source projects, and academic labs to identify emerging trends and future platform opportunities. - Partner with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to support researcher adoption and long-term engagement. - Represent researcher needs internally by translating academic feedback into actionable insights for product roadmaps, developer programs, education, and platform strategy. - Support NVIDIA participation in major AI, ML, and systems research venues through technical content, workshops, university engagements, and lab-facing programs. What we need to see: - PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or a related technical field, or equivalent research depth. - 5+ years of experience - Deep expertise in foundational AI, including LLMs, multimodal models, generative AI, reasoning, post-training, model evaluation, or AI systems research. - Strong understanding of modern AI model development across the lifecycle, including pretraining, fine-tuning, post-training, optimization, evaluation, deployment, and model serving. - Hands-on experience with AI research stacks such as PyTorch, JAX, distributed training frameworks, inference systems, model serving platforms, evaluation pipelines, and GPU-accelerated workflows. - Technical fluency in scalable AI systems, including distributed training, parallelism strategies, checkpointing, memory optimization, batching, scheduling, latency, throughput, and cost-performance tradeoffs. - Familiarity with methods that improve model efficiency and performance, such as quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data generation, RLHF/RLAIF, and preference optimization. - Ability to engage top academic labs on frontier research challenges, including scaling behavior, compute efficiency, model quality, benchmark methodology, reproducibility, reliability, and research impact. - Demonstrated research credibility through publications, open-source contributions, academic collaborations, technical leadership, or direct work on frontier AI systems. Ways to stand out from the crowd: - Experience with NVIDIA AI platforms, including CUDA, CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NIM, NeMo, Megatron, Transformer Engine, NCCL, DGX, NVLink, InfiniBand, or NVIDIA AI Enterprise. - Established relationships with leading AI labs, academic institutions, research institutes, benchmark communities, or major open-source AI projects. - Track record translating frontier AI research into demos, tutorials, reference architectures, workshops, technical blogs, or developer enablement programs. - Experience presenting at venues such as NeurIPS, ICML, ICLR, CVPR, AAAI , or related research workshops. - Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you. NVIDIA is committed to foster a diverse work environment and proud to be an equal opportunity employer! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What You'll Be Doing: - The software architecture group at NVIDIA has openings for a Deep Learning Communication Architect. We scale the DNN models and training/inference frameworks to systems with hundreds of thousands of nodes. - Optimizing communication performance: Identify and eliminate bottlenecks in data transfer and synchronization during distributed deep learning training and inference. - Designing efficient communication protocols: Develop and implement communication algorithms and protocols tailored for deep learning workloads, minimizing communication overhead and latency. - Hardware and software co-craft: Collaborate with hardware and software teams to craft systems that effectively apply high-speed interconnects (e.g., NVLink, InfiniBand, SPC-X) and communication libraries (e.g., MPI, NCCL, UCX, UCC, NVSHMEM). - Exploring innovative communication technologies: Research and evaluate new communication technologies and techniques to enhance the performance and scalability of deep learning systems. - Developing and implementing solutions: Build proofs-of-concept, conduct experiments, and perform quantitative modeling to validate and deploy new communication strategies. What We Need to See: - A Ph.D., Masters, or BS in Computer Science (CS), Electrical Engineering (EE), Computer Science and Electrical Engineering (CSEE), or a closely related field or equivalent experience. - 6+ years of experience in Building DNNs, Scaling of DNNs, Parallelism of DNN frameworks, or deep learning training and inference workloads. - Experience in evaluating, analyzing, and optimizing LLM training and inference performance of state-of-the-art models on cutting-edge hardware. - Deep understanding of parallelism techniques, including Data Parallelism, Pipeline Parallelism, Tensor Parallelism, Expert Parallelism, and FSDP. - Understanding of the emerging serving architectures like Disaggregated Serving and inference servers like Dynamo and Triton - Proficiency in developing code for one or more deep neural network (DNN) training and Inference frameworks, such as PyTorch, TensorRT-LLM, vLLM, SGLang. - Strong programming skills in C++ and Python. - Familiarity with GPU computing, including CUDA and OpenCL, and familiarity with InfiniBand and RoCE networks. CUDA and OpenCL, and familiarity with InfiniBand and RoCE networks. Ways to Stand Out from the Crowd: - Prior contributions to one or more DNN training and Inference frameworks as part of your previous work experience. - Deep understanding and contributions to the scaling of LLMs on large-scale systems. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and talented people in the world working for us. If you're creative and passionate about developing cloud services we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA’s accelerated computing ecosystem thrives on deep engagement with developers. We offer a wide range of libraries, tools, APIs, and frameworks to help developers achieve faster results and optimize energy consumption. We are looking for a Developer Advocate on Physical AI and Robotics with a passion for Robotics, Embedded devices, and AI. This role is pivotal in helping developers craft the next generation of intelligent robots. Your responsibilities will include crafting compelling demos, sharing code and how-to guides, and connecting with the developer community on a deeper level. We aim to expand the developer network by building applications on NVIDIA’s platform, including Isaac Sim, Isaac Lab, Newton, and MJWarp. The platform uses NVIDIA and other ecosystem tools. We need a candidate who understands developers and collaborates with marketing to launch innovative technology. What You’ll Be Doing: - Crafting engaging, developer-focused materials such as demos, blogs, presentations, and videos. - Connecting with developers, researchers, and students at both online and in-person events. - Developing and deploying the complete robotics lifecycle, from simulation to validation and final deployment on physical platforms using NVIDIA GPUs. - Combining robotics applications with Generative AI, using widely-adopted tools and frameworks. - Defining strategic roadmaps for content and events, providing mentorship and ensuring successful outcomes across different organizations. - Collaborating with engineering, product management, and marketing teams to identify high-impact developer needs and build technical solutions. What We Need To See: - Bachelor’s, Master’s, or Ph.D. in Computer Science, Software Engineering, Robotics, or a related technical area (or equivalent experience). - 8+ years of professional experience in Software Engineering, Application Engineering, Robotics, or embedded devices. - Proven experience developing applications for various robotic platforms including humanoids, wheeled robots, quadrupeds, and UAVs. - Established experience in communicating complex technical subjects to engineers and producing developer-focused content. - Hands-on experience with tools and frameworks such as ROS, OpenCV, NVIDIA JetPack, MuJoCo Warp, Newton, Isaac Sim, and PyTorch. - Solid knowledge or hands-on experience with contemporary AI, particularly Generative AI, to tackle challenges in robotics using agentic AI workflow. - A proactive, adaptable, and collaborative teammate. Passionate about developing new technologies in a dynamic environment with the latest technology. - Understanding of evangelism and how to effectively engage with developer communities. Ways To Stand Out From The Crowd: - Experience with Generative AI tools and frameworks used in the Physical AI community. - Skilled in crafting technical content, like blog posts, tutorial videos with a strong technical background including research publications. - Active involvement in developer communities. Experience in running events, webinars, hackathons, or peer-reviewed submissions is a plus. - Self-motivated individual capable of prioritizing tasks according to mission goals. - Strong communication abilities in front of large audiences. The capability to tell stories and write succinctly while explaining complex ideas clearly is highly valued. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. We're looking for a passionate AI research scientist with deep quantum computing expertise to path-find the future of fault-tolerant quantum systems powered by machine learning. Quantum computing is a strategic priority for NVIDIA, and our goal is to accelerate the entire ecosystem. As a Sr. Applied Research Scientist in Quantum Computing, you will architect and build AI solutions at the heart of fault-tolerant quantum computing—spanning quantum error correction, decoding, calibration, and beyond. You will research and develop open AI models, curated datasets, and rigorous benchmarks that advance the state of the art and empower the broader quantum community. Your research will help translate cutting-edge theory into practice by fine-tuning models for specific quantum error-correcting codes and hardware platforms, while collaborating with multi-functional teams across Product, Engineering, and Applied Research to integrate AI into next-generation Accelerated Quantum Supercomputers! Do you love developing new technology, enjoy working with collaborative people and teams around the world, and operating at the speed of light? If yes, we would love to hear from you! What you'll be doing: - Design and architect AI/ML models—including deep neural networks, graph neural networks, transformers, and reinforcement-learning agents—for quantum error correction, syndrome decoding, logical operation synthesis, and real-time calibration in fault-tolerant quantum systems. - Develop cutting-edge AI techniques for quantum computing that contribute to NVIDIA's open model efforts across the quantum ecosystem. - Help create high-quality, large-scale datasets for quantum error correction and quantum system characterization, including simulated and hardware-derived syndrome data, enabling the community to train and evaluate AI models at scale. - Collaborate with quantum hardware teams to collect and structure hardware-derived training data, enabling domain-adapted models that improve over time as hardware matures. - Co-design AI solutions with quantum hardware and software teams, ensuring decoders and calibration models meet latency and throughput requirements for real-time operation inside fault-tolerant feedback loops. - Communicate research findings through top-tier venues and collaborate with academic and industry partners to advance the field, while championing a culture of rapid innovation, technical depth, and creative problem solving. What we need to see: - Degree in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a related field (Ph.D. strongly preferred); equivalent demonstrated experience also considered. - 8+ years of combined experience in quantum computing and/or AI/ML research, with a track record of high-impact contributions in at least one of these domains. - Deep expertise in machine learning and deep learning—including model architecture design, training at scale, and evaluation—applied to scientific or engineering problems. - Strong background in Quantum Information Science, including quantum error correction, fault-tolerant protocols, and quantum noise models. - Excellent communication skills and the ability to collaborate effectively with multi-functional teams across research, engineering, and product. Ways to stand out from the crowd: - Hands-on experience developing learned decoders or AI-driven calibration systems for quantum hardware (superconducting qubits, trapped ions, or other platforms). - Experience with large-scale model training and fine-tuning—including parameter-efficient fine-tuning (LoRA, QLoRA, adapters) and domain adaptation for scientific AI models. - Proficiency with CUDA and NVIDIA GPU programming for accelerating quantum simulation, AI model training, or real-time decoding workloads. - Experience with high-performance computing (HPC) environments and distributed training frameworks (e.g., PyTorch Distributed, Megatron-LM, or JAX pmap) for large-scale quantum AI workloads. - Passion to drive AI innovations into NVIDIA software and hardware products that support the broader quantum computing ecosystem. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is looking for a Machine Learning (ML) Engineer to join the GPU accelerated Apache Spark team. Apache Spark is the most popular data processing engine in data centers for running large scale workloads for ETL, SQL, and ML/DL model training and inference pipelines, spanning many domains and use cases. NVIDIA GPUs offer a promising avenue for significantly speeding up and/or lowering the cost of running Apache Spark applications at massive scales. You will work with the open source community to accelerate Apache Spark with GPUs. You will apply the latest ML/AI methods to empower enterprises to migrate Spark workloads onto GPUs at scale. What you’ll be doing: - Design and implement machine learning solutions for performance prediction and optimization of GPU accelerated enterprise Apache Spark workloads. - Develop advanced algorithms and adaptive systems to continuously improve the performance of Apache Spark workloads on GPUs. - Develop AI-based agents and tools to assist with fixing system issues and application optimization. - Collaborate with key partners and customers on the deployment of complex machine learning solutions in various environments. - Maintain deep domain expertise by knowing the latest published advances in ML systems and algorithms. - Provide technical mentorship and leadership in data science and machine learning to a team of engineers. What we need to see: - BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science or a closely related field. - 12+ years of professional experience in designing, implementing, and productionizing high-quality ML/DL solutions. - 5+ experience as technical lead in ML model development. - Proven hands-on experience (2+ years) with large-scale data processing platforms, such as Apache Spark. - Proven ability to employ modern tooling and sound techniques for all aspects of crafting, deploying, and maintaining machine learning models. - Excellent programming skills in Python and Python data science related libraries like numpy, pandas, scikit-learn, scipy, pytorch, and tensorflow. - Deep experience with sophisticated ML methodologies, including LLM/GenAI, reinforcement learning, and adaptive, on-line ML systems. - Strong expertise in feature engineering, feature importance assessment, and developing boosted tree model solutions (e.g., XGBoost). Ways to stand out from the crowd: - Understanding of the internal workings and architecture related to Apache Spark. - Familiarity with NVIDIA GPUs and CUDA. - Experience coding in Scala, Java, and/or C++. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and dedicated people in the world working for us. If you are passionate about what you do, creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

At NVIDIA, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. As a Developer Technology Engineer, you will be at the forefront of innovation, working with leading industry partners and exciting OSS projects to help them adopt groundbreaking advancements in AI and accelerated computing on NVIDIA RTX. This role offers an outstanding opportunity to collaborate with world-class talent and make a significant contribution to the next era of enterprise and consumer AI. What you'll be doing: - Work closely with internal engineering and product teams and external app developers on solving local end-to-end AI GPU deployment challenges on the NVIDIA RTX AI platform. - Apply powerful profiling and debugging tools for analyzing most demanding GPU-accelerated end-to-end AI applications to detect insufficient GPU utilization resulting in suboptimal runtime performance. - Conduct hands-on trainings, develop sample code and host presentations to give good guidance on efficient end-to-end AI deployment targeting optimal runtime performance on NVIDIA ARM-based SoCs. - Improve Windows LLM & GenAI user experience on NVIDIA RTX by working on feature and performance enhancements of OSS software, including but not limited to projects like GGML, Llama.cpp, Ollama, ONNX Runtime. - Collaborate with GPU driver and architecture teams as well as NVIDIA research to influence next generation GPU features by providing real-world workflows and giving feedback on partner and customer needs. - Providing technical leadership and mentorship to junior engineers, encouraging an inclusive and high-performing team environment. What we need to see: - A proven track record of 8+ years of professional experience in local GPU deployment, profiling and optimization. - Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field. - Strong proficiency in C/C++, Python, software design, programming techniques.. - Familiarity with and development experience on the Windows operating system. - Experience working with open-source LLM and GenAI software. - Experience with CUDA and NVIDIA's Nsight GPU profiling and debugging suite. - Some travel is required for conferences and for on-site visits with external partners. - Strong problem-solving skills and the ability to work both independently and collaboratively in a fast-paced environment. - Excellent interpersonal and communication skills and a passion for keeping track with the latest advancements in AI technology. Ways to stand out from the crowd: - Experience with GPU-accelerated AI inference driven by NVIDIA APIs, specifically cuDNN, CUTLASS, TensorRT. - Confirmed expert knowledge in Vulkan and / or DX12. - Detailed knowledge of the latest generation GPU architectures. - Experience with AI deployment on NPUs and ARM architectures. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value. What you’ll be doing: - Develop and improve the technical design, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art CNN and transformer-based architectures where appropriate. - Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception. - Build efficient, production-grade deep learning models: define objectives with the team, select and prototype architectures, run experiments, and follow best practices for training and evaluation, using techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA). - Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial. - Contribute to the data strategy for perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, including model-assisted workflows (e.g., active learning, auto-labeling, vision-language models (VLMs)) and model-in-the-loop tooling. - Collaborate with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale. What we need to see: - PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Proven experience in data-driven development, including close collaboration with data, labeling, and ground-truth teams on data strategy, labeling quality, and iterative model improvement. - Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams. Ways to stand out from the crowd: - Experience designing and deploying perception solutions for autonomous driving or robotics using camera-based deep learning at scale. - Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms, including optimization for latency, memory, and compute constraints, and experience with modern architectures such as CNNs and transformers, plus familiarity with techniques like large-scale pretraining, parameter-efficient fine-tuning (e.g., LoRA), or vision-language models (VLMs). - Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS). - Deep understanding of 3D computer vision fundamentals, including camera modeling and calibration (intrinsic and extrinsic), multi-view geometry, and 3D representations, ideally with experience applying these concepts in transformer-based 3D or BEV perception pipelines. - Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Do you want to help drive the development of CPU technology for architectures used for artificial intelligence (AI) / deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and autonomous vehicles? Come join the CPU performance architecture team and help us push performance boundaries for all our CPU products! What   you'll   be doing : - Study workloads for a wide range of markets, including CSP, HPC,   AI / DL , and autonomous vehicles. - Develop infrastructure to visualize CPU performance bottlenecks on important workloads. - Develop performance analysis tools. - Analyze and debug performance scaling bottlenecks on multi-core and multi-socket CPU and CPU/GPU systems. - Work with CPU   architects   to improve future CPU and system designs based on your findings. What we need to see: - BS/MS in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. - Experience with data   visualization techniques   and Python programming . - Familiarity   with   compiler concepts . - Understanding of   modern web development   technologies   ( JavaScript , D3 , and Django)   and modern software development methodologies (CI/CD). - 12+ years of relevant experience. - Experience with CPU workloads and performance analysis. - Knowledge   of CPU microarchitecture. Ways to stand out from the crowd: - PhD or research experience - Experience with performance programming and software optimization. - Knowledge of GPU-accelerated workloads. - Experience with Kubernetes, enterprise security protocols, and SQLite. NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries — from robotics and autonomous vehicles to healthcare and climate research . With the introduction of the Grace CPU Superchip , and more recently, the announcement of the Vera CPU , NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA’s broader technology stack, enabling faster AI model training,   agentic use-cases,   efficient data processing, and scalable cloud deployments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 26, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Join us at NVIDIA as we redefine the future of robotics and AI! Our Isaac Lab team is on a mission to propel our flagship platform for robot learning to new heights. This is an outstanding chance to be part of an ambitious, world-class team pushing the boundaries of what's possible in autonomous systems training. You'll be immersed in a diverse and encouraging environment where innovation and collaboration are at the forefront. What you will be doing: - Develop innovative features for our platform, such as perception-in-the-loop reinforcement learning, multi-agent / multi-task learning, VLA and RL integration. - Participate in the open-source development of Isaac Lab, engaging with the robotics industrial and research communities. - Scale training massively in the cloud while ensuring flawless performance through extensive benchmarking, profiling, and optimizations. - Collaborate with research and engineering teams across NVIDIA to enable brand new research for the next generation of humanoid robots. What we need to see: - Currently pursuing an MS or PhD degree in Computer Science, Robotics, or a related field. - Extensive experience in software development with Python and deep-learning software stacks like Pytorch, Tensorflow, or Jax. - Proven experience in robotics and simulation workflows, including reinforcement learning, imitation learning, motion planning, and trajectory optimization. Ways to stand out from the crowd: - Prior experience with Isaac Sim, Isaac Lab, Isaac Gym, or Mujoco. - Successfully trained a robot in simulation and deployed the policy sim-to-real. - Publications in major AI and robotics conferences.

NVIDIA is seeking a Software Engineering Manager to lead a high-performing software engineering team developing advanced networking management tools that power the next generation of AI and Machine Learning infrastructure. In this role, you will drive execution across complex, cross-functional initiatives spanning software, networking, infrastructure, and system engineering teams. You will be responsible for delivering scalable, reliable, and high-performance management solutions that enable seamless operation of NVIDIA’s cutting-edge ML platforms at scale. This is a highly visible leadership role requiring a combination of strong technical depth, organizational leadership, and execution excellence. You will influence architecture, product direction, engineering processes, and team growth while helping shape technologies at the forefront of AI infrastructure innovation. What You’ll Be Doing: - Lead and grow a team of software engineers developing next-generation networking management and orchestration tools - Own execution and delivery of major cross-functional initiatives involving multiple engineering teams and stakeholders - Drive technical strategy, architecture decisions, and long-term roadmap planning for networking management solutions - Partner closely with software, networking, firmware, hardware, DevOps, and system architecture teams to deliver scalable and reliable solutions - Establish engineering best practices, operational excellence, and high development standards across the team - Mentor engineering leaders and senior engineers, fostering technical growth and leadership development - Balance technical leadership with organizational execution in a fast-paced and rapidly evolving environment - Provide hands-on technical guidance, debugging support, and architectural direction when required What We Need to See: - Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent practical experience - 8+ overall years of software industry experience, including 3+ years managing software engineering teams - Proven experience leading complex, large-scale software projects across multiple teams and disciplines - Strong software development background in C/C++ - Demonstrated ability to drive execution, resolve ambiguity, and deliver high-quality products in fast-paced environments - Strong system-level thinking and problem-solving skills - Excellent communication, collaboration, and stakeholder management skills - Proven ability to influence technical direction and organizational priorities Ways to Stand Out from the Crowd: - Experience with Linux, networking technologies, or distributed systems - Experience building infrastructure, management, orchestration, or observability platforms - Experience leading geographically distributed or multi-disciplinary engineering teams - Background in AI/ML infrastructure, datacenter technologies, or high-performance computing environments - Experience scaling organizations, mentoring managers or technical leaders, and driving organizational maturity

We are now looking for Senior Signal & Power Integrity Engineer. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Drive board/system level signal and power integrity requirements - Lead board/system SI/PI design activities, including PCB stackup/material selection, design guide implementation, layout review, and post-layout analysis - Work closely with Architecture, ASIC, Mixed Signal, Package, and PCB Design teams to design and ensure system SI/PI performance meets expectation before Gerber out, also work closely with Design Validation teams to support SI/PI failure analysis - Develop novel algorithms & new methodologies to improve SI/PI modeling efforts - Work with Application Engineering teams to support customers w/ SI/PI questions - VNA & TDR measurements to support model correlation efforts and improve confidence in design stage What we need to see: - MS/BS in EE or equivalent experience - Minimum 3+ years of experience as a SI/PI engineer - Deep understanding of electromagnetics, specifically electromagnetic waves including transmission line theory and via properties - Proficient with HFSS, Sigrity, Hspice, and/or other simulation tools - Experienced with Cadence Allegro PCB designer and Constraints Manager - Understanding of high volume manufacturing variations and impact to channel signal integrity - Exposure to lab measurements including VNA & TDR experience - Passionate about SI/PI work - Good written & verbal interpersonal skills in English Ways to stand out from the crowd: - Familiarity with NRZ/PAM-4 signaling schemes - Exposure to interface timing budgets and system modeling - Familiarity with high-speed I/O design concepts including clock generation, transmitter & receiver design, and equalization schemes - PDN analyses including model generation and time domain simulation - Experience w/ Matlab, Python, and C as well as exposure to package design

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production — over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we're looking for the engineer to lead that charge. In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows, driving initiatives from concept to deployment. If you combine deep technical expertise with a hands-on approach and an aim to push the boundaries of what's possible, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed! What you'll be doing: - Designing and implementing AI/LLM-powered systems to improve post-silicon validation, automation, and workflow efficiency within semiconductor validation environments. - Collaborating with multi-functional engineering teams to find opportunities for AI integration and performance optimization. - Evaluating emerging frameworks, architectures, and tools to improve efficiencies powered by artificial intelligence across the organization. - Establish and maintain data-driven indicators to quantify AI impact, identify performance gaps, and drive continuous improvement across systems. What we need to see: - BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services. - 2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment. - Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala. - Demonstrated experience with deep learning frameworks like   PyTorch   or TensorFlow, and hands-on experience with agentic and orchestration tools including   NeMo   Agent Toolkit,   LangChain , Semantic Kernel,   AutoGen ,   CrewAI , or n8n. - Proven track record with deploying, monitoring, and debugging scalable AI/ML models. - Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction. - Ability to balance multiple simultaneous projects. - Excellent problem-solving, communication, and collaboration skills. Ways to stand out from the crowd: - Familiarity with modern AI technologies and methodologies for crafting and launching LLMs with ability to translate innovative AI research into practical, high-impact production tools. - Experience with building and deploying orchestration agents managing hundreds to thousands of tools. - Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers). - Experience working within a silicon development environment, with exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing/power analysis. - Experience debugging complex system-level issues involving HW/SW interactions, including leadership or ownership in driving root cause analysis of silicon or feature-level issues. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family   www.nvidiabenefits.com