{"schemaVersion":"jobsearcher.job.v1","id":"ddf5b75eb560fd305e95d646","url":"https://jobsearcher.com/jobs/ddf5b75eb560fd305e95d646","canonicalUrl":"https://jobsearcher.com/jobs/ddf5b75eb560fd305e95d646","title":"Senior Deep Learning Frameworks CUDA Software Engineer","description":"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.\r\nWhat You Will Be Doing\r\nIntegrate new CUDA features and Runtime abstractions in AI frameworks: from PoC to performance analysis to production\r\nPerform deep analysis of AI workloads and frameworks to identify requirements and opportunities to innovate in the lower layers of the stack. Collaborate hands-on with teams working on the latest AI models.\r\nOwn and drive improvements in the AI Compiler-Runtime interface to build speed-of-light multi-GPU multi-node solutions.\r\nDesign fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.\r\nInfluence the roadmap of core CUDA to facilitate building next-gen DL frameworks.\r\nCollaborate with a very dynamic team across multiple time zones.\r\nCollaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and frameworks that enhance performance and programmability.\r\nDevelop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.\r\nWrite clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products.\r\nWhat We Need To See\r\nBS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).\r\n8+ years of relevant industry experience or equivalent academic experience after completed degree.\r\nDevelopment experience with Deep Learning Frameworks such as PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang\r\nRapid prototyping and development with Python, C++, CUDA or related DSLs\r\nSolid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)\r\nExperience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)\r\nUnderstanding of HPC/AI communication concepts\r\nGood understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)\r\nAdaptability and passion to learn new frameworks and tools\r\nFlexibility to work and communicate effectively across different teams and timezones\r\nWays To Stand Out From The Crowd\r\nDeep expertise in the performance internals and execution graphs of major deep learning autograd, training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron, MaxText, etc.).\r\nHands-on experience with CUDA, specific communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline parallelism, tensor parallelism).\r\nExpertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc).\r\nBackground in deep learning compilers, both graph-level and codegen (e.g., Triton, XLA, torch compile)\r\nExperience with programming for compute & communication overlap in distributed runtime\r\nYour 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.\r\nYou will also be eligible for equity and benefits.\r\nApplications for this job will be accepted at least until July 1, 2026.\r\nNVIDIA uses AI tools in its recruiting processes.\r\nNVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. We do not discriminate 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.\r\nJ-18808-Ljbffr","company":"NVIDIA","rawCompany":"nvidia","city":"Wausau","state":"WI","isRemote":false,"isActive":false,"createdAt":"2026-08-09T00:29:38.058Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Deep Learning Frameworks CUDA Software Engineer","description":"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.\r\nWhat You Will Be Doing\r\nIntegrate new CUDA features and Runtime abstractions in AI frameworks: from PoC to performance analysis to production\r\nPerform deep analysis of AI workloads and frameworks to identify requirements and opportunities to innovate in the lower layers of the stack. Collaborate hands-on with teams working on the latest AI models.\r\nOwn and drive improvements in the AI Compiler-Runtime interface to build speed-of-light multi-GPU multi-node solutions.\r\nDesign fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.\r\nInfluence the roadmap of core CUDA to facilitate building next-gen DL frameworks.\r\nCollaborate with a very dynamic team across multiple time zones.\r\nCollaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and frameworks that enhance performance and programmability.\r\nDevelop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.\r\nWrite clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products.\r\nWhat We Need To See\r\nBS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).\r\n8+ years of relevant industry experience or equivalent academic experience after completed degree.\r\nDevelopment experience with Deep Learning Frameworks such as PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang\r\nRapid prototyping and development with Python, C++, CUDA or related DSLs\r\nSolid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)\r\nExperience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)\r\nUnderstanding of HPC/AI communication concepts\r\nGood understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)\r\nAdaptability and passion to learn new frameworks and tools\r\nFlexibility to work and communicate effectively across different teams and timezones\r\nWays To Stand Out From The Crowd\r\nDeep expertise in the performance internals and execution graphs of major deep learning autograd, training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron, MaxText, etc.).\r\nHands-on experience with CUDA, specific communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline parallelism, tensor parallelism).\r\nExpertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc).\r\nBackground in deep learning compilers, both graph-level and codegen (e.g., Triton, XLA, torch compile)\r\nExperience with programming for compute & communication overlap in distributed runtime\r\nYour 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.\r\nYou will also be eligible for equity and benefits.\r\nApplications for this job will be accepted at least until July 1, 2026.\r\nNVIDIA uses AI tools in its recruiting processes.\r\nNVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. We do not discriminate 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.\r\nJ-18808-Ljbffr","datePosted":"2026-08-09T00:29:38.058Z","dateModified":"2026-08-09T00:29:38.058Z","hiringOrganization":{"@type":"Organization","name":"NVIDIA","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Wausau","addressRegion":"WI","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ddf5b75eb560fd305e95d646"},"url":"https://jobsearcher.com/jobs/ddf5b75eb560fd305e95d646"}}