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. We are looking for a highly motivated senior software engineer for an exciting role in our communication libraries and network software team. The position will be part of a fast-paced crew that develops and maintains software for complex heterogeneous computing systems that power disruptive products in High Performance Computing and Deep Learning. What you will be doing: Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM. Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components. Creating proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware. What we need to see: M.S./Ph.D. degree in CS/CE or equivalent experience. 5+ years of relevant experience. Excellent C/C++ programming and debugging skills. Strong experience with Linux. Expert understanding of computer system architecture and operating systems. Experience with parallel programming interfaces and communication runtimes. Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment. Ways to stand out from the crowd: Deep understanding of technology and passionate about what you do. Experience with CUDA programming and NVIDIA GPUs. Knowledge of high-performance networks like InfiniBand, iWARP etc. Experience with HPC applications. Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc. Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix 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 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 September 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.
09/25/2026
Full time
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. We are looking for a highly motivated senior software engineer for an exciting role in our communication libraries and network software team. The position will be part of a fast-paced crew that develops and maintains software for complex heterogeneous computing systems that power disruptive products in High Performance Computing and Deep Learning. What you will be doing: Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM. Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components. Creating proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware. What we need to see: M.S./Ph.D. degree in CS/CE or equivalent experience. 5+ years of relevant experience. Excellent C/C++ programming and debugging skills. Strong experience with Linux. Expert understanding of computer system architecture and operating systems. Experience with parallel programming interfaces and communication runtimes. Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment. Ways to stand out from the crowd: Deep understanding of technology and passionate about what you do. Experience with CUDA programming and NVIDIA GPUs. Knowledge of high-performance networks like InfiniBand, iWARP etc. Experience with HPC applications. Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc. Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix 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 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 September 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 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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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.
09/25/2026
Full time
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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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 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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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.
09/25/2026
Full time
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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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 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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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.
09/25/2026
Full time
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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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 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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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.
09/25/2026
Full time
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 looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. Influence the roadmap of communication libraries - NCCL & NVSHMEM. Collaborate with a very dynamic team across multiple time zones. What we need to see: B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ software engineering and HPC/AI experience Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) 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: Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 September 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 is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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.
09/25/2026
Full time
NVIDIA is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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 is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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.
09/25/2026
Full time
NVIDIA is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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 is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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.
09/25/2026
Full time
NVIDIA is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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 is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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.
09/25/2026
Full time
NVIDIA is seeking a Senior Software Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware, Linux kernel development, and middleware development, with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you'll be doing: Design and develop software solutions for data center servers including Linux kernel modifications, device drivers, and system optimizations for GB200 and next-gen platforms. Lead hardware bring-up activities, BSP development, and hardware-software co-design for Cloud Service Provider deployments. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Collaborate with cross-functional teams in designing end-to-end solutions spanning firmware, OS, middleware, and applications with focus on AI/ML and HPC workloads. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Expert knowledge of Linux kernel internals, device drivers, communication protocols (PCIe, USB, Ethernet). Deep understanding of computer architecture, microprocessor concepts, and expert knowledge of ARM (aarch64) and x86 architectures. Ability to debug kernel crash dumps and all types of lock-up issues. Hands-on experience with GDB, kdump, and eBPF tracing to debug multiprocessor systems. Good understanding of ARM and Intel assembly. Strong understanding of PCIe virtualization and IOMMU. Deep understanding of NUMA architectures including memory topology, processor-memory locality, and performance optimization for multi-CPU systems in data center environments. Strong programming skills in C/C++, Python, plus experience with virtualization, Kubernetes, and cloud-native architectures. Skilled in complex system-level debugging, performance analysis, and test design. BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience). 10+ years of system software development experience. Ways to stand out from the crowd: Experience with GPU computing (CUDA), deep learning workloads Expertise in Out of Band and In-band management architectures Knowledge of Memory fabric and CXL architectures 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 have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, hardworking and self-motivated, we want to hear from you! Do you want to join a team of highly motivated and experienced program managers who drive the successful introduction of NVIDIA's next generation GPU/CPU based products? We work closely with internal leaders in Software, Hardware, Firmware, Marketing and Operations to ensure the SW team delivers outstanding products while operating across multiple functional units and all levels of management to achieve Time-To-Market. As part of the team, your knowledge of driver, firmware, diagnostics and the SW stack development processes and priorities will enable you to swiftly make the course adjustments needed to keep these complex projects on track! 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 September 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.
About the Role Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale. If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You'll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory. You'll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency. Shape the core inference backbone that powers Together AI's frontier models. Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation. Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale. Partner with world-class researchers to bring new model architectures into production. Collaborate with and contribute to the open source community, shaping the tools that advance the industry. A culture of deep technical ownership and high impact - where your work makes models faster, cheaper, and more accessible. Competitive compensation, equity, and benefits. Responsibilities Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods. Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers. Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling - including smart rate limiting and regulation - to ensure fairness and consistent experience across all users. Engineer trade-offs between latency and throughput to serve diverse workloads efficiently. Optimize prefix caching to reduce model compute and speed up responses. Collaborate with ML researchers to bring new model architectures into production at scale. Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations. Requirements 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices. Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems. Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance. Expert-level programming in one or more of: Rust, Go, Python, or TypeScript. Knowledge of modern LLMs and generative models and how they are served in production is a plus. Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy. Experience with Kubernetes or container orchestration is a strong plus. Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus. Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $290,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at
09/24/2026
Full time
About the Role Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale. If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You'll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory. You'll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency. Shape the core inference backbone that powers Together AI's frontier models. Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation. Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale. Partner with world-class researchers to bring new model architectures into production. Collaborate with and contribute to the open source community, shaping the tools that advance the industry. A culture of deep technical ownership and high impact - where your work makes models faster, cheaper, and more accessible. Competitive compensation, equity, and benefits. Responsibilities Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods. Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers. Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling - including smart rate limiting and regulation - to ensure fairness and consistent experience across all users. Engineer trade-offs between latency and throughput to serve diverse workloads efficiently. Optimize prefix caching to reduce model compute and speed up responses. Collaborate with ML researchers to bring new model architectures into production at scale. Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations. Requirements 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices. Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems. Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance. Expert-level programming in one or more of: Rust, Go, Python, or TypeScript. Knowledge of modern LLMs and generative models and how they are served in production is a plus. Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy. Experience with Kubernetes or container orchestration is a strong plus. Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus. Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $290,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at
