Senior Deep Learning Engineer, CUDA

🕒 August 4

🏄 California, Texas – Remote

🏄 California – Remote 🤠 Texas – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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NVIDIA

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10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 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.

📋 Description

• 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 requirements and opportunities for lower-layer innovation • Collaborate hands-on with teams working on the latest AI models • Drive improvements in the AI compiler-runtime interface for high-performance multi-GPU, multi-node solutions • Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads • Influence the roadmap of core CUDA for next-generation deep learning frameworks • Collaborate with a dynamic team across multiple time zones • Co-design systems and frameworks with AI researchers, hardware and software architects, kernel and compiler authors, and CUDA driver experts • Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms • Write clean, effective, and maintainable code • Transition exploratory prototypes into open-source releases, upstream framework integrations, internal tools, or commercial products

🎯 Requirements

• BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience) • 8+ years of relevant industry experience or equivalent academic experience after completed 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 • Solid grasp of AI models, parallelisms, 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 • Good understanding of computer system architecture, HW-SW interactions, and operating systems principles • Adaptability and passion to learn new frameworks and tools • Flexibility to work and communicate effectively across different teams and time zones • Deep expertise in performance internals and execution graphs of major deep learning autograd, training, and inference frameworks • Hands-on experience with CUDA, communication libraries such as NCCL, MPI, or UCX, and distributed machine learning techniques • Expertise in training, distributed inference, MoE, reinforcement learning, or kernel authoring on CUDA, Triton, or cuTe • Background in deep learning compilers, including graph-level and code generation technologies such as Triton, XLA, or torch compile • Experience programming for compute and communication overlap in distributed runtime

🏖️ Benefits

• Equity • Benefits

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