Senior Data Center Performance Engineer, Benchmarking and Optimization

Nvidia

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Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
38 days ago
Freshness
Confirmed live today

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Data Center Performance Engineer, Benchmarking and Optimization

JOB TITLE: Senior Data Center Performance Engineer - Benchmarking and Optimization As a Senior Data Center Performance Engineer - Benchmarking and Optimization, you will join the team responsible for ensuring data center solutions deliver industry-leading performance for accelerated computing workloads. You will design and execute comprehensive benchmarking strategies for data center platforms, characterizing real-world AI training, inference, and HPC workloads at scale. Your daily responsibilities include defining key performance indicators, building automation tools for monitoring, and identifying bottlenecks across compute, memory, network, and storage subsystems. You will utilize Linux perf, NVIDIA Nsight Systems, CUDA, Python, C++, and shell scripting to drive improvements. The role requires deep knowledge of computer architecture, InfiniBand, RoCE, and NVLink. You will collaborate with cross-functional teams to optimize system configurations and provide architectural recommendations for future generation systems.

What you'll do

  • Design and execute comprehensive performance benchmarking strategies for data center platforms and products.
  • Characterize real-world AI training, inference, and HPC workloads at scale.
  • Define, track, and report key performance indicators including throughput, latency, efficiency, and scaling.
  • Build automation tools and frameworks for performance monitoring and analysis.
  • Identify and analyze performance bottlenecks across compute, memory, network, and storage subsystems.
  • Drive performance improvements through system tuning, configuration optimization, and architectural recommendations.

What we're looking for

  • M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
  • 8+ years of experience in performance engineering or system architecture.
  • Deep understanding of computer architecture, hardware-software interaction, and computing at-scale.
  • Strong proficiency in performance profiling tools such as Linux perf and NVIDIA Nsight Systems.
  • Familiarity with GPU computing, parallel programming (CUDA), and HPC networking technologies (InfiniBand, RoCE, NVLink).
  • Programming skills in Python, C++, and shell scripting with excellent analytical and problem-solving abilities.
  • Experience with AI/ML frameworks (PyTorch, TensorFlow, JAX) and knowledge of MPI, NCCL, and distributed training (preferred).
  • Familiarity with containers, cloud provisioning, and scheduling tools (Docker, Kubernetes, SLURM) (preferred).

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