Ai Inference Performance Engineer - New College Grad 2026

Invidia

Us, CA, United States
Base: 124,000 usd - 195,500 usd (level 2), 152,000...
Deep learning inference optimization
Python or c++ programming
Experience with dl frameworks
We optimize and benchmark GenAI inference on NVIDIA's latest accelerators, defining the industry’s performance standards across language models, video generation, and speech workloads

Job Summary

  • We optimize and benchmark GenAI inference on NVIDIA's latest accelerators, defining the industry’s performance standards across language models, video generation, and speech workloads.
  • This team sits at the intersection of GPU performance engineering and public accountability, driving industry benchmark results and collaborating with multiple teams to push performance to its extreme.
  • NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer, offering equity and benefits alongside competitive base salaries.

Matching Summary

We optimize and benchmark GenAI inference on NVIDIA's latest accelerators, defining the industry’s performance standards across language models, video generation, and speech workloads.

Salary

Base: 124,000 USD - 195,500 USD (Level 2), 152,000 USD - 241,500 USD (Level 3); Bonus/Equity: Eligible for equity; Benefits: Eligible for benefits

Skills & Requirements

Must-have

  • Deep learning inference optimization
  • Python or C++ programming
  • Experience with DL frameworks
  • GPU performance engineering
  • Distributed inference design
  • Profiling and performance analysis

Nice-to-have

  • Experience with LLM frameworks
  • Performance modeling and debugging
  • Scale-out inference orchestration
  • Kernel development expertise
  • GPU programming with CUDA
  • Cross-functional technical leadership

Key Requirements

  • BS, MS, or PhD in related fields
  • 2+ years relevant software development
  • Strong software design and engineering skills
  • Proven performance improvement track record
  • Deep understanding of LLM/VLM architectures

Work Rights

Not specified

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