Senior AI Compiler Engineer, MLIR

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI API Algorithms @ 4 CUDA @ 6 Debugging @ 6 Deep Learning @ 4 GPU @ 4 JAX @ 4 LLVM @ 4 Mentoring @ 4 OpenCL @ 6 Performance Analysis @ 6 PyTorch @ 4 Python @ 6

Details

NVIDIA is hiring a Senior AI Compiler Engineer to build an MLIR-based AI compiler that powers NVIDIA's inference engine end to end. The role focuses on performance, fast builds, low memory use, and Ahead-of-Time and Just-in-Time usability across data center and edge environments.

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.
Contribute to general software engineering work.

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.
At least 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.

Preferred Qualifications

Understanding of deep learning models, algorithms, and frameworks such as PyTorch and JAX.
Experience with GPU kernel generation targeting high performance and fast build times.
Proficiency in GPU architecture with CUDA or OpenCL programming experience.
Experience mentoring early-career engineers and interns.

Benefits

Competitive salary.
Equity and benefits.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.

Applications will be accepted at least until August 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.