Careers at NVIDIA

The NVIDIA Networking Diagnostics team is seeking a highly motivated and experienced engineer. This person must have hands-on technical expertise to develop critical diagnostic tools for our newest, world-leading networking platforms. This position offers the opportunity to have a real impact in a dynamic, technology-focused company, impacting data centers and high-performance computing (HPC) clusters across the world. We are looking for independent engineers who excel in a fast-paced environment and are passionate about ensuring the stability of next-generation hardware. What you'll be doing: Design & Implement: Architect and develop high-performance diagnostic tools and frameworks using Python, tailored for NVIDIA’s latest networking platforms. Performance Optimization: Drive end-to-end development focusing on software that performs efficiently, ensuring diagnostic suites can handle high-throughput data and real-time monitoring without latency. System Diagnostics: Take charge of developing features that bridge the gap between complex hardware behaviors and software-level diagnostics. Collaborative Problem Solving: Partner with hardware, firmware, and driver teams to address real-world challenges that demand innovative solutions and a customer-centric approach. Autonomous Execution: Own the full software development lifecycle of diagnostic features, from initial hardware specification to deployment in dynamic environments. What we need to see: B.Sc or equivalent experience in Computer Engineering, Computer Science, Electrical Engineering, or a related field. 5+ years of hands-on experience in the software development lifecycle, with a proven track record in performance-critical systems. Python Mastery: Advanced programming skills in Python, with a focus on writing optimized, efficient, and scalable code for hardware interfacing. Networking & HW Background: Solid understanding of networking protocols (TCP/IP, InfiniBand, or Ethernet) and hardware-level interaction. Linux Expertise: Strong familiarity with Linux environments, associated debugging tools, and system-level performance tuning. Strong analytical and debugging skills. A highly collaborative great teammate who is also self-motivated, well-organized, and capable of working independently in a fast paced environment. Ways to stand out from the crowd: Performance Tooling: Experience with performance profiling, optimization, and low-level hardware communication (e.g., PCIe, I2C). Low-Level Knowledge: Background in C/C++, RT embedded development, or driver development within a Linux environment. Technical Leadership: Experience leading technical projects or mentoring team members in a dynamic setting. Problem Solving: Confirmed experience in root-causing complex system-level issues and solving customer-facing hardware challenges. 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.

The NVIDIA Networking Diagnostics team is seeking a highly motivated and experienced engineer. This person must have hands-on technical expertise to develop critical diagnostic tools for our newest, world-leading networking platforms. This position offers the opportunity to have a real impact in a dynamic, technology-focused company, impacting data centers and high-performance computing (HPC) clusters across the world. We are looking for independent engineers who excel in a fast-paced environment and are passionate about ensuring the stability of next-generation hardware. What you'll be doing: Design & Implement: Architect and develop high-performance diagnostic tools and frameworks using Python, tailored for NVIDIA’s latest networking platforms. Performance Optimization: Drive end-to-end development focusing on software that performs efficiently, ensuring diagnostic suites can handle high-throughput data and real-time monitoring without latency. System Diagnostics: Take charge of developing features that bridge the gap between complex hardware behaviors and software-level diagnostics. Collaborative Problem Solving: Partner with hardware, firmware, and driver teams to address real-world challenges that demand innovative solutions and a customer-centric approach. Autonomous Execution: Own the full software development lifecycle of diagnostic features, from initial hardware specification to deployment in dynamic environments. What we need to see: B.Sc or equivalent experience in Computer Engineering, Computer Science, Electrical Engineering, or a related field. 5+ years of hands-on experience in the software development lifecycle, with a proven track record in performance-critical systems. Python Mastery: Advanced programming skills in Python, with a focus on writing optimized, efficient, and scalable code for hardware interfacing. Networking & HW Background: Solid understanding of networking protocols (TCP/IP, InfiniBand, or Ethernet) and hardware-level interaction. Linux Expertise: Strong familiarity with Linux environments, associated debugging tools, and system-level performance tuning. Strong analytical and debugging skills. A highly collaborative great teammate who is also self-motivated, well-organized, and capable of working independently in a fast paced environment. Ways to stand out from the crowd: Performance Tooling: Experience with performance profiling, optimization, and low-level hardware communication (e.g., PCIe, I2C). Low-Level Knowledge: Background in C/C++, RT embedded development, or driver development within a Linux environment. Technical Leadership: Experience leading technical projects or mentoring team members in a dynamic setting. Problem Solving: Confirmed experience in root-causing complex system-level issues and solving customer-facing hardware challenges. 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.

NVIDIA is shaping the next era of computing, where AI, accelerated computing, and high-speed networking come together to power the world’s most advanced AI systems. Within NVIDIA, the Networking Business Unit (NBU) builds the high-speed interconnect technologies — Ethernet, InfiniBand, NVLink, and BlueField DPUs — that connect thousands of GPUs into a single AI supercomputer. NVIDIA is looking for a Technical Lead to join our Network System Validation group and lead the validation of advanced networking solutions across complex AI cluster environments. This is a deeply hands-on technical leadership role, combining ownership of the validation roadmap with technical mentoring and engineering excellence. You will develop validation methodologies and automation frameworks, while working hands-on on debugging, performance analysis, and cutting-edge AI networking technologies at scale. Join us to help push NVIDIA’s networking technologies to their limits and shape how next-generation AI infrastructure is validated. What you’ll be doing: Review system and product requirements, design validation methodologies, develop and implement comprehensive test plans , functional and performance, for networking technologies in large-scale AI cluster solutions Develop and maintain benchmarks, automation tools and scripts for test execution, environment setup, log collection, and data analysis. Lead end-to-end investigation of complex issues by reproducing real-world scenarios, analyzing logs, telemetry, packet captures, and system metrics to identify functional issues and performance bottlenecks, triaging problems across the hardware and software stack, and driving them to root cause and resolution Read and understand source code (C/C++/Python) to investigate defects, validate fixes, and improve logging, instrumentation, and debugging capabilities Collaborate deeply with software and hardware development teams to debug networking technologies, including NCCL, RoCE, RDMA, and related software components using targeted experiments and code inspection Profile and research AI training and inference workloads, correlating application behavior with network and system telemetry to identify scalability and performance limitations Document findings, communicate technical results, and continuously improve validation methodologies, automation environments, and engineering processes What we need to see: B.Sc. / B.A. in Computer Science, Electrical Engineering, or equivalent experience 8+ years of experience in networking, system validation, or related domains Proven experience debugging complex production systems by forming hypotheses, designing experiments, and driving issues to root cause Ability to read, debug, and reason about C/C++ code (Rust or Go a plus) Strong scripting and automation experience using Python, Bash, and/or Ansible Deep understanding of distributed systems: concurrency, consistency models, fault tolerance, and large-scale system performance under stress Ability to drive technical alignment across teams, communicate tradeoffs clearly, and make high-quality architectural decisions at speed Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines Ways to stand out from the crowd: Experience with large-scale clusters or distributed systems Familiarity with NVIDIA networking solutions ( ConnectX , SpecX , BlueField ) Background in performance analysis, Kubernetes, or cloud environments Background in chaos test ing , fault injection, or simulation systems We have some of the most forward-thinking and hardworking people 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, 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.

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.

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.

NVIDIA DGX Cloud provides the infrastructure and software platform that enables enterprises to build, train, and deploy AI at scale. As demand for accelerated computing grows, effective capacity management is critical to delivering reliable customer experiences while maximizing the utilization of constrained GPU infrastructure. We are looking for a Senior Software Engineer to design and build the systems that connect customer demand, infrastructure supply, reservations, allocation, and utilization across DGX Cloud environments. You will work with engineering, product, operations, finance, and business teams to transform complex capacity data and operational processes into scalable software and automated decision-making. What You’ll Be Doing: Design and build distributed services and data pipelines for capacity planning, allocation, reservations, and utilization. Develop a unified model of available, committed, and forecasted GPU capacity across cloud providers, regions, clusters, and products. Automate capacity-management workflows currently dependent on manual analysis and coordination. Build APIs, tools, and integrations that enable other DGX Cloud systems and teams to make capacity-aware decisions. Improve forecasting, scenario planning, and operational visibility by combining demand signals with infrastructure supply data. Establish monitoring, data-quality controls, and service-level indicators for capacity systems. Lead technical design reviews, establish engineering standards, and mentor other engineers. Diagnose complex production issues and improve the reliability, performance, and scalability of capacity-management services. What We Need to See: BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field. 5+ years of software engineering experience building production systems. Strong programming experience in languages such as Python, Go, Java, or similar. Experience designing distributed systems, backend services, APIs, and data-processing pipelines. Experience working with cloud infrastructure, Kubernetes, compute platforms, or large-scale resource-management systems. Strong understanding of data modeling, system integration, observability, and production operations. Ability to turn ambiguous business and operational requirements into clear technical designs. Strong communication skills and experience working across engineering and non-engineering organizations. Ways to Stand Out From the Crowd: Experience with GPU infrastructure, AI/ML platforms, schedulers, cluster management, or accelerated computing. Experience building capacity planning, inventory, supply-and-demand, quota, reservation, or resource-allocation systems. Familiarity with optimization, forecasting, simulation, or operations-research techniques. Experience managing infrastructure across multiple cloud providers or geographically distributed environments and serving as a technical lead for cross-functional, business-critical initiatives. Demonstrated success improving infrastructure utilization while maintaining reliability and customer commitments. 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. NVIDIA is looking for phenomenal people like you to help us accelerate 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 dedicated people in the world working for 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 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 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.