NVIDIA
Senior Compiler Engineer, AI Inference Platforms
$152K–$242K
US, CA, Santa Clara +4 · Senior · Full-time · Posted Feb 23, 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.
- Education
- Bachelor’s, Master’s or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience.
About the job
Develops and optimizes NVIDIA’s deep-learning compiler to improve inference performance, build time, memory use, and ease of use across platforms.
What you'll do
- Analyze deep-learning networks and develop compiler optimization algorithms.
- Collaborate with deep-learning framework and GPU architecture teams to accelerate software.
- Define public APIs and implement compiler techniques, performance optimizations, and analysis for AI workloads and future GPUs.
What they ask for
- Bachelor’s, Master’s or Ph.D. in Computer Science, Computer Engineering, a related field or equivalent experience.
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- 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.
Nice to have
- Proficiency in CPU and/or GPU architecture; CUDA or OpenCL programming experience.
- Understanding of deep-learning models, algorithms, and frameworks such as PyTorch or JAX; GPU kernel authoring and performance analysis using tools such as Nsight Compute.
Pay
152,000 USD - 241,500 USD (base salary)
Tools
MLIR, LLVM, XLA, Triton, C/C++, Python, CUDA, OpenCL
AI focus
Builds and optimizes a deep-learning inference compiler for AI workloads across data centers, personal devices, automotive, and robotics.
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