Senior GPU Systems Performance Architect

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 184,000 - 357,000; Full time

Job summary

NVIDIA in Santa Clara, CA seeks a Senior Systems Performance Engineer to build profiling infrastructure that spans CPU and GPU, tackling multi-terabyte EDA workloads and high-throughput kernels.

You will benchmark memory access, analyze cache behavior, and detect warp divergence and bottlenecks with Nsight and other tools, while developing predictive models to guide hardware procurement and cloud choices.

Qualifications

• A BS/MS/PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience)
• 8+ years of relevant experience and at least 5 years involved in systems-level performance analysis
• Strong knowledge of GPU profiling tools and CPU/GPU interaction patterns
• Experience with distributed compute environments and job schedulers

Responsibilities

• Architecting and maintaining custom profiling frameworks for CPU and GPU environments
• Conducting deep-dive benchmarking of EDA applications to characterize memory access patterns, cache hit rates, and IPC
• Using GPU profilers to detect GPU-side inefficiencies such as warp divergence, sub-optimal occupancy, and bottlenecks
• Developing tools to monitor and attribute memory usage in multi-terabyte EDA builds and optimize memory pooling
• Developing predictive models to guide hardware procurement and cloud instance selection

Skills

CUDA programming

Nsight profiling

Perf

eBPF

VTune

Valgrind

Kubernetes

Slurm

LSF

GPU profiling

Education

BS/MS/PhD in CS/EE or related field

Tools

Nsight Systems/Compute

Perf

VTune

Valgrind

Kubernetes

Slurm

LSF

Docker

Job description

NVIDIA in Santa Clara, CA seeks a Senior Systems Performance Engineer to build profiling infrastructure that spans CPU and GPU, tackling multi-terabyte EDA workloads and high-throughput kernels.

You will benchmark memory access, analyze cache behavior, and detect warp divergence and bottlenecks with Nsight and other tools, while developing predictive models to guide hardware procurement and cloud choices.