Senior Deep Learning Engineer, CUDA

Job not on LinkedIn

🕒 August 4

🏄 California, Texas – Remote

🏄 California – Remote 🤠 Texas – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

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 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

🎯 Requirements

• 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

🏖️ Benefits

• Equity • Benefits