Senior Deep Learning Framework Engineer

Job not on LinkedIn

🕒 January 23

🏄 California, North Carolina, +2 more states – Remote

🏄 California – Remote 🌲 North Carolina – Remote 🍂 Massachusetts – Remote 🤠 Texas – Remote

💵 $152k - $241.5k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

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👻 Ghost score 36%

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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 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.

🎯 Requirements

• B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ 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

🏖️ Benefits

• equity • benefits