Senior AI Compiler Engineer (MLIR) — Equity & Impact

NVIDIA; California (MO); On-site; USD 152,000 - 288,000; Full time

Job summary

NVIDIA is seeking an experienced compiler/MLIR engineer to develop graph representations and optimizations for future GPU architectures. You will collaborate with framework and hardware teams to enable new model patterns and upcoming GPU features, defining APIs and MLIR dialects and implementing kernel generation for neural networks.

The role requires strong C/C++/Python skills, a track record in performance analysis and compiler optimizations, and an ability to work independently in a

Qualifications

• 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, XLA, and LLVM.
• Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and testing.
• Ability to work independently, define project goals and scope, and lead your own development efforts.
• Strong interpersonal skills and the ability to thrive in a fast-moving, dynamic, product-oriented team.

Responsibilities

• Develop MLIR-based graph representations and optimizations for future GPU architectures.
• Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural features.
• Define APIs and MLIR dialects, conduct performance optimizations and analysis, implement compiler optimizations and kernel generation for neural networks, and contribute to other general software engineering work.

Skills

C/C++

Python

Software design

Debugging

Performance analysis

Independent work

Leadership

Education

Bachelor's / Master's / PhD in CS/CE

Tools

MLIR

XLA

LLVM

Job description

NVIDIA is seeking an experienced compiler/MLIR engineer to develop graph representations and optimizations for future GPU architectures. You will collaborate with framework and hardware teams to enable new model patterns and upcoming GPU features, defining APIs and MLIR dialects and implementing kernel generation for neural networks.

The role requires strong C/C++/Python skills, a track record in performance analysis and compiler optimizations, and an ability to work independently in a