
10,000+ employees
Founded 1993
đĽ Healthcare
đ Manufacturing
đ¤ Artificial Intelligence
Healthcare ⢠Manufacturing ⢠Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
đĽ 9 minutes ago
đ California, Texas â Remote
đľ $184k - $356.5k / year
â° Full Time
đ Senior
đ¤ Machine Learning Engineer
đŚ H1B Visa Sponsor
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10,000+ employees
Founded 1993
đĽ Healthcare
đ Manufacturing
đ¤ Artificial Intelligence
Healthcare ⢠Manufacturing ⢠Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
⢠Integrate new CUDA features and runtime abstractions in AI frameworks from proof of concept through performance analysis to production ⢠Analyze AI workloads and frameworks to identify lower-level requirements and innovation opportunities ⢠Collaborate hands-on with teams working on the latest AI models ⢠Drive improvements in the AI compiler-runtime interface for multi-GPU and multi-node solutions ⢠Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads ⢠Influence the core CUDA roadmap for next-generation deep learning frameworks ⢠Collaborate across multiple time zones with AI researchers, hardware and software architects, kernel and compiler authors, and CUDA driver experts ⢠Co-design systems and frameworks that improve performance and programmability ⢠Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms ⢠Write clean, effective, maintainable code and transition prototypes into open-source releases, framework integrations, internal tools, or commercial products
⢠BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience ⢠8+ years of relevant industry experience or equivalent academic experience after completing the degree ⢠Development experience with deep learning frameworks such as PyTorch and JAX, and inference engines such as TRT-LLM, vLLM, and SGLang ⢠Rapid prototyping and development with Python, C++, CUDA, or related DSLs ⢠Strong understanding of AI models, parallelism, and/or compiler technologies such as torch.compile ⢠Experience conducting performance benchmarking on AI clusters ⢠Familiarity with at least one performance profiler toolchain, such as PyTorch Profiler or NVIDIA Nsight Systems ⢠Understanding of HPC/AI communication concepts ⢠Understanding of computer system architecture, hardware-software interactions, and operating systems principles ⢠Adaptability and willingness to learn new frameworks and tools ⢠Ability to work and communicate effectively across different teams and time zones ⢠Preferred additional expertise in deep learning framework performance internals and execution graphs ⢠Preferred hands-on experience with CUDA, NCCL, MPI, UCX, and distributed machine learning techniques ⢠Preferred expertise in training, distributed inference, mixture-of-experts, reinforcement learning, or kernel authoring with CUDA, Triton, or cuTe ⢠Preferred background in deep learning compilers such as Triton, XLA, and torch.compile ⢠Preferred experience programming compute and communication overlap in distributed runtimes
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