NVIDIA
Senior AI Compiler Engineer, Algorithms and Code-Generation
$152K–$242K
US, CA, Santa Clara +4 · Senior · Full-time · Posted Jul 14, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, TX, Remote
US, WA, Remote
US, CA, Remote - Experience
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Education
- Bachelor’s, master’s, or Ph.D. in Computer Science, Computer Engineering, or a related field, or equivalent experience.
About the job
Develops compiler optimization algorithms and performance improvements for NVIDIA’s deep-learning compiler and AI inference workloads.
What you'll do
- Analyze deep-learning networks and develop compiler optimization algorithms.
- Use CUDA to analyze and debug GPU performance bottlenecks.
- Define public APIs and implement compiler techniques and performance optimizations for AI workloads and future NVIDIA GPUs.
What they ask for
- Experience with compiler technologies such as MLIR, LLVM, XLA, or Triton.
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Ability to work independently, define project goals and scope, and lead development efforts.
- Strong interpersonal skills and ability to work in a dynamic, product-oriented team.
Nice to have
- Proficiency in CPU and/or GPU architecture, especially modern NVIDIA GPUs such as Hopper and Blackwell.
- Understanding of deep-learning models, algorithms, and frameworks such as PyTorch and JAX.
Pay
152,000 USD - 241,500 USD (base salary)
Tools
CUDA, C/C++, Python, MLIR, LLVM, XLA, Triton, PyTorch
AI focus
Build and optimize a deep-learning compiler for AI inference, including compiler techniques and performance optimizations for AI workloads.
Model-written summary · the original posting is authoritative