NVIDIA
Senior Deep Learning Compiler Engineer
$152K–$242K
US, CA, Santa Clara +5 · Senior · Full-time · Posted Oct 9, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, TX, Remote
US, WA, Remote
US, CA, Remote
US, WA, Redmond - 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, related field or equivalent experience.
About the job
Develop deep learning compiler optimizations and infrastructure to improve inference performance, build time, memory use, and usability across NVIDIA platforms.
What you'll do
- Analyze deep learning networks and develop compiler optimization algorithms.
- Collaborate with software framework and hardware architecture teams to accelerate deep learning software.
- Define public APIs and implement compiler infrastructure, performance optimizations, and related software engineering work.
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.
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Ability to work independently 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; CUDA or OpenCL programming experience.
- Experience with resource-constrained systems, MLIR, XLA, TVM, LLVM, deep learning frameworks such as PyTorch, or high-performance GPU kernel generation.
Pay
152,000 USD - 241,500 USD (base salary)
Tools
C/C++, Python, CUDA, OpenCL, MLIR, XLA, TVM, LLVM
AI focus
Develop compiler infrastructure and optimizations for deep learning inference workloads and models.
Model-written summary · the original posting is authoritative