Senior Systems Software Engineer, GPU Performance at Scale

What you'll do

• Implement performance practices and tools to validate and improve multiple datacenter products concurrently.
• Align next-generation AI workloads with datacenter hardware including GPUs, CPUs, and networking components.
• Develop engineering solutions to provide continuous insights into the performance of AI workloads in evolving environments.
• Decompose complex performance or stability issues into minimal reproduction cases to identify root causes.
• Analyze, debug, and resolve critical firmware and software issues to optimize high-performance AI workloads at scale.
• Architect and optimize large-scale performance platforms by collaborating with HPC, OS, CPU, and GPU specialists.
• Create improved workflows and new solutions for researchers, developers, and customers.

What we're looking for

• Proven understanding of accelerated computing software stacks including CUDA.
• Experience with modern cloud and container-based enterprise computing architectures, preferably with Slurm.
• Strong programming and scripting skills in C, C++, Python, and Bash.
• Deep expertise in systems architecture and the impact of various components on performance.
• Experience with Linux-based operating systems and container technology, preferably with Docker.
• Experience supporting high-performance computing or deep learning in engineering or academic research communities.
• A BS in Engineering, Mathematics, Physics, or Computer Science is required; an MS or PhD is desirable.
• At least 8 years of applicable experience are desired for advanced candidates.