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NVIDIA

Designs the chips and software that power AI

Senior Software Engineer - CUTLASS Performance

Full-Time
$152k - $241.5k/yr+ Equity
Senior
Master's, PhD
Austin, TX, USA+4 moreMore locations: Redmond, WA, USA | Santa Clara, CA, USA | Durham, NC, USA | Hillsboro, OR, USA
In Person
Software Engineering
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
  • 3+ years of relevant industry experience.
  • Strong programming skills in Python and C++.
  • Experience in software performance analysis and optimization.
  • Deep understanding of computer architecture and familiarity with GPUs or similar parallel processing architectures.
Responsibilities
  • Benchmark the performance of state-of-the-art deep learning models’ inference and training passes to identify key GPU kernel and fusion opportunities.
  • Identify gaps between theoretical and realized performance, and suggest software improvements or model adjustments to resolve them.
  • Develop tooling to automate the benchmarking, analysis, and performance optimization loop to push the limit of CUTLASS kernel performance within DL networks.
  • Be the authoritative resource on kernel performance in the team and engage with teams across NVIDIA including GPU architecture, DL frameworks, and QA as the performance representative for the CUTLASS team.
Desired Qualifications
  • Deep understanding of state-of-the art DL model architectures.
  • Hands-on experience with performance benchmarking of DL frameworks like PyTorch, JAX, SGLang, vLLM, TRT-LLM, or others.
  • Experience in developing performance models and performance regression systems.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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