Senior Systems Performance Engineer

Nvidia

Confirmed live today Trusted

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$136,000–$212,750 / yr
Employment
Full-time
Posted
53 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $167k
This role $174k
$125k $222k
below market most similar roles pay here above market

This role pays more than 54% of similar roles. Most pay $136,358–$196,750 — the blue band above. At the midpoint, this role pays about $174k versus about $167k for comparable roles.

Based on 240 similar postings.

Employer

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 Systems Performance Engineer

JOB TITLE: Senior Systems Performance Engineer The Senior Systems Performance Engineer joins the DGX Server Product Engineering Team to work with hardware and software engineers on developing and implementing complex automated test plans for GPU accelerated computing products. The role involves system architecture, design, performance modeling, and estimation across new models and packages. Key responsibilities include enabling GPU SKU bring up, validation, and model enablement while developing system level stress and performance testing strategies using Deep Learning and AI applications. Required technical skills include Dynamo, TensorRT, Slurm, and BCM, with preferred knowledge of vLLM and SG Lang. Candidates must demonstrate proficiency in Cuda, Cublas, Cutlass, and Python programming. The work focuses on validating and debugging complex systems, including datacenter products involving system management, security, networking, and storage.

What you'll do

  • Develop and implement complex automated test plans for GPU accelerated computing products.
  • Perform system architecture, design, performance modeling, and estimation across new models and packages.
  • Enable GPU SKU bring up, validation, and model enablement.
  • Develop system-level stress and performance testing strategies using Deep Learning and AI applications.
  • Develop and run real-world ML and LLM workloads.
  • Debug complex systems and perform hardware lab testing.
  • Run simulators and write code using Python.
  • Manage datacenter products including system management, security, networking, and storage.

What we're looking for

  • Ability to work on site in a hardware lab environment 5 days a week.
  • BSEE or BSCE or equivalent experience.
  • 5+ years of experience in validating and debugging complex systems.
  • Experience developing and running real-world ML/LLM workloads.
  • Mandatory skills in Dynamo, TensorRT, Slurm, and BCM.
  • Proficiency in Cuda, Cublas, Cutlass, and Python programming.
  • Deep understanding of computing architectures and experience with datacenter products.
  • Background with x86/Arm server architectures and accelerated GPU computing (preferred).

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