Senior Systems Software Engineer, GPU Performance at Scale

What you'll do

• Lead the implementation of performance practices and tools for large-scale GPU infrastructure.
• Align next-generation AI workloads with datacenter builds for GPUs, CPUs, and networking hardware.
• Develop engineering solutions to provide continuous performance insights for AI workloads in evolving environments.
• Decompose high-complexity performance or stability issues into minimal reproduction cases to identify root causes.
• Analyze, debug, and resolve critical firmware and software issues to maximize AI workload performance.
• Architect and optimize large-scale performance platforms by engaging with HPC, OS, and GPU compute specialists.
• Develop improved workflows and new solutions in collaboration with researchers, developers, and customers.

What we're looking for

• Proven understanding of accelerated computing software stacks (CUDA).
• Strong programming and scripting experience in C, C++, Python, and Bash.
• Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred.
• Experience with container technology and Linux-based OSes, with Docker preferred.
• Experience supporting high-performance computing or deep learning in engineering or academic research communities.
• BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience).
• MS or PhD with 8+ years of applicable experience (preferred).
• End-to-end GPU performance engineering from the profiler to systems analysis (preferred).