Description

Lead performance validation and optimization for large-scale GPU infrastructure, AI workloads, and datacenter products.

This role is remote.

Responsibilities

• Implement performance practices and methodologies to validate and improve datacenter products concurrently.
• Align next-generation AI workloads with NVIDIA GPUs, CPUs, and networking hardware builds.
• Decompose high-complexity performance or stability issues into minimal reproduction cases to identify root causes.
• Develop engineering solutions and tools for continuous insights into AI workload performance and regressions.
• Collaborate with SW/FW teams (BMC/SBIOS/OS/drivers) to analyze, debug, and resolve critical firmware and software issues.

Required Skills

• 8+ years of applicable experience in systems architecture and accelerated computing software stacks.
• Deep understanding of CUDA and modern cloud/container-based enterprise computing architectures.
• Strong programming and scripting proficiency in C, C++, Python, and Bash.
• Experience with Linux-based OSes and container technology (Docker preferred).
• Practical experience with Slurm scheduling systems.
• Background supporting high-performance computing or deep learning in engineering or academic research.
• BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience).

Preferred Skills

• MS or PhD in a relevant technical field.
• Experience engaging with hardware and firmware teams for early-stage product alignment.

Key Skills

Education

Any Graduate