Careers at NVIDIA

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. Join a team that analyzes large-scale datacenter workloads on GPU-accelerated clusters. You will turn telemetry and workload data into clear findings and visuals. You will partner with OS, container, GPU, and systems engineers. When useful, you will apply machine learning and deep learning techniques for categorization and forecasting. These will be coordinated into tools the team actually uses. What you’ll be doing: Analyze large-scale workloads and infrastructure signals to find application and platform improvement opportunities. Work with high-dimensional data: spot trends, tie changes to known events, summarize conclusions, and communicate results to engineers and leadership. Partner with the team to clarify questions, scope analyses, and document methods so others can extend your work. Build and maintain practical visualizations and lightweight implementations (e.g. ML/DL for classification/prediction) inside existing software workflows. What we need to see: 5+ years analyzing complex datasets, debugging data issues, and communicating trends clearly. BS or MS in Engineering, Mathematics, Physics, Computer Science, or equivalent experience. Strong Python and JavaScript; Comfortable being responsible for an analysis end-to-end. Hands-on use of telemetry / observability stacks (e.g. Grafana, Elasticsearch, Splunk). Shown grasp of core ML concepts; quick learner; strong analytical and problem-solving skills. Collaboration and communication. Ways to stand out from the crowd: TensorFlow or PyTorch Linux and HPC / large-scale or performance-sensitive environments Experience visualizing high-dimensional problems Diligent, action-biased analysis style 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 also offers a comprehensive benefits package. We provide health care coverage, dental and vision, 401(K), including company matching and after tax contributions, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company paid holidays, paid sick leave, vacation leave, professional time off, life and disability protection. 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 October 2, 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. Join a team that analyzes large-scale datacenter workloads on GPU-accelerated clusters. You will turn telemetry and workload data into clear findings and visuals. You will partner with OS, container, GPU, and systems engineers. When useful, you will apply machine learning and deep learning techniques for categorization and forecasting. These will be coordinated into tools the team actually uses. What you’ll be doing: Analyze large-scale workloads and infrastructure signals to find application and platform improvement opportunities. Work with high-dimensional data: spot trends, tie changes to known events, summarize conclusions, and communicate results to engineers and leadership. Partner with the team to clarify questions, scope analyses, and document methods so others can extend your work. Build and maintain practical visualizations and lightweight implementations (e.g. ML/DL for classification/prediction) inside existing software workflows. What we need to see: 5+ years analyzing complex datasets, debugging data issues, and communicating trends clearly. BS or MS in Engineering, Mathematics, Physics, Computer Science, or equivalent experience. Strong Python and JavaScript; Comfortable being responsible for an analysis end-to-end. Hands-on use of telemetry / observability stacks (e.g. Grafana, Elasticsearch, Splunk). Shown grasp of core ML concepts; quick learner; strong analytical and problem-solving skills. Collaboration and communication. Ways to stand out from the crowd: TensorFlow or PyTorch Linux and HPC / large-scale or performance-sensitive environments Experience visualizing high-dimensional problems Diligent, action-biased analysis style 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 also offers a comprehensive benefits package. We provide health care coverage, dental and vision, 401(K), including company matching and after tax contributions, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company paid holidays, paid sick leave, vacation leave, professional time off, life and disability protection. 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 October 2, 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.

For more than 25 years, NVIDIA has driven innovation in computer graphics, PC gaming, and accelerated computing. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re harnessing the boundless possibilities of AI to build 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. DSX OS is NVIDIA's open source foundation for AI infrastructure. It is a growing portfolio of engineering teams building in the open. A project earns real open source standing when its team has actually adopted the practices, its governance model works day to day, and outside contributors have a clear, well-run path into the project. You will be responsible for governance design, community infrastructure, contributor tooling, and the plan that carries a project through its first months in the open. This role owns building that process. It means driving adoption, designing governance, building the infrastructure and automation a community runs on, and the roadmap that takes DSX OS projects from newly public to actively, sustainably built with the community. What you'll be doing: Drive adoption of open source standard methodologies. Partner with product teams to make sure open source hygiene and governance practices are consistently applied in everyday work. Design open source governance. Work with each team to help them design a governance model that fits how they actually work — who owns what, how decisions get made, how contributors get a real path in. Grow active contribution. Help teams turn interested outsiders into real contributors — code, docs, ideas — building the kind of community that actually strengthens the project. Provision and run community infrastructure. Own infrastructure for community engagement — Slack, community meetings, collaboration spaces — for every project as it comes online, and own its ongoing lifecycle. Build the post-launch plan. Develop and run the 30/60/90-day plan supporting a repo’s shift from just open source to an active, well-governed project. It addresses community, transparency, governance, marketing, and security posture soon after launch. Design the contributor path and its first-pass review. Build isolated, contributor-safe CI that validates external pull requests without touching internal infrastructure, and the end-to-end path from starter issue to contribution guide to automated review — including a check that screens each PR for quality signal before a maintainer looks at it. Monitor community health. Track engagement across community channels, run the operational side of external events, and build automated metrics so program health is visible without manual reporting. Turn engagements into playbooks. Package every readiness engagement into a reusable playbook, so each subsequent project moves faster than the last. What we need to see: 12+ years of relevant experience Bachelors degree or equivalent experience Background with driving adoption of open source practices across multiple engineering teams and turning a stated policy into how teams actually work day to day Experience crafting open source governance including pathways for contributors, maintainer roles, and decision-making processes that's lightweight enough for teams to actually use Strong software engineering skills, with a track record of building the automation an open source program depends on: CI checks, PR review tooling, metrics pipelines Hands-on experience with agentic coding tools (e.g., Claude Code, Copilot, Cursor) as part of your actual engineering workflow, not just casual use Experience running open source community programs with infrastructure, events, contributor engagement and with real accountability for participation and turnout An ownership mentality where you take responsibility for managing a team's open source adoption and its community, end to end Ways to stand out from the crowd: Familiarity with the patterns that make an open source repo credible such as README structure, contribution docs, governance files, issue templates and gained from working across many different projects, not just one Direct experience contributing to or maintaining an open source project. You know what it feels like on the other side of a PR, an issue queue, or a governance vote Experience building spam or low-quality-submission detection for an open contribution surface that solve anti-abuse, moderation, or automated triage systems Experience producing or running technical events such as conference talks, workshops, meetups where you owned the logistics, not just presented Technical writing experience aimed at an external audience such as contributor guides, onboarding docs, or public-facing project documentation that a stranger could follow without help 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 hard-working and dedicated people in the world working for us and, due to outstanding 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. #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 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 2, 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 Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target. In this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you! What You’ll Be Doing: Lead, mentor, and develop your team. Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance. Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines. Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed. Identify performance targets for new platforms, establish performance testing and fix performance regressions. Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms. Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations. What We Need to See: PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience). 8+ years of overall experience developing high-performance numerical software. 3+ years leading and mentoring software engineering teams. Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python. Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning. Strong communication, collaboration, and documentation habits. Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA. Ways to Stand Out from the Crowd: Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads). Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers). Proven track record using Agentic AI to boost your efficiency and code quality. Experience with cross-platform software development and platform bring-up across multiple architectures. Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262). #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 October 2, 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 Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target. In this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you! What You’ll Be Doing: Lead, mentor, and develop your team. Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance. Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines. Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed. Identify performance targets for new platforms, establish performance testing and fix performance regressions. Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms. Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations. What We Need to See: PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience). 8+ years of overall experience developing high-performance numerical software. 3+ years leading and mentoring software engineering teams. Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python. Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning. Strong communication, collaboration, and documentation habits. Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA. Ways to Stand Out from the Crowd: Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads). Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers). Proven track record using Agentic AI to boost your efficiency and code quality. Experience with cross-platform software development and platform bring-up across multiple architectures. Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262). #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 October 2, 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.