Overview
Develop and tune the compute infrastructure stack allocating NVIDIA Grace Blackwell (GB) and Vera Rubin (VR) resources to AI workloads. Scale GPU clusters across hardware generations to thousands of accelerators and beyond. Use operational data and workload insights to inform the compute (GPU and CPU) roadmap for large-scale AI research. Partner with model-development teams to improve the infrastructure used to train and serve AI models. Find practical ways around roadblocks and deliver improvements rapidly, iterating with users in a fast-paced, design-driven environment. A bachelor's degree in computer science or a related technical field and at least six years of engineering experience writing code in languages such as C, C++, Python, Go, or JavaScript; or equivalent practical experience. Significant additional engineering experience, with a master's degree or equivalent practical expe
Full job description
Full Job Description
Develop and tune the compute infrastructure stack allocating NVIDIA Grace Blackwell (GB) and Vera Rubin (VR) resources to AI workloads. Scale GPU clusters across hardware generations to thousands of accelerators and beyond. Use operational data and workload insights to inform the compute (GPU and CPU) roadmap for large-scale AI research. Partner with model-development teams to improve the infrastructure used to train and serve AI models. Find practical ways around roadblocks and deliver improvements rapidly, iterating with users in a fast-paced, design-driven environment. A bachelor's degree in computer science or a related technical field and at least six years of engineering experience writing code in languages such as C, C++, Python, Go, or JavaScript; or equivalent practical experience. Significant additional engineering experience, with a master's degree or equivalent practical experience, building production software and distributed systems. Experience with Ray, Kubernetes, Kueue, Volcano, or another AI-focused system for scheduling, scaling, or fault tolerance is especially relevant.
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