Senior Systems Software Engineer - GPU Performance at Scale

NVIDIA has been transforming computer graphics and accelerated computing for over 25 years, focusing on AI to define the next era of computing. They are seeking a Senior Systems Software Engineer to drive innovation in GPU performance at scale, contributing to advanced computing hardware and software while collaborating with various teams to enhance workflows and solutions.

Responsibilities:

• Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently
• Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware. Engage early with HW/FW/SW/platform internal and customer teams
• Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions
• Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause
• Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools. Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale

Requirements:

• Proven understanding of accelerated computing software stacks (CUDA)
• Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred
• Strong programming and scripting experience in C/C++/Python/Bash
• Deep expertise in systems architecture and the impact of various components on performance
• 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
• Strong teamwork and communication skills, coupled with results-focused analytical abilities
• BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 8+ years of applicable experience
• End-to-end GPU performance engineering from the profiler to systems analysis
• Linux systems programming and optimization experience
• Exposure to virtualization techniques and cloud platform solutions
• Experience with scheduling and resource management systems
• Experience with large-scale HPC environments