Senior Compiler Engineer, AI Inference Platforms

at Nvidia

USD 152,000-241,500 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 @ 4 Debugging @ 6 Deep Learning @ 4 GPU @ 6 JAX @ 4 LLVM @ 4 Mentoring @ 4 OpenCL @ 4 Performance Analysis @ 6 PyTorch @ 4 Python @ 6 Robotics

Details

NVIDIA is hiring a software engineer for its Deep Learning and AI Compiler team. The team develops compiler technology that powers inference across data centers, personal devices, automotive, and robotics. The compiler is designed to deliver leading inference performance, fast build times, reduced memory footprints, and ease of use through both Ahead-of-Time and Just-in-Time compilation.

Responsibilities

Analyze deep learning networks and develop compiler optimization algorithms.
Collaborate with deep learning software framework teams and GPU architecture teams to accelerate the next generation of deep learning software.
Define public APIs, develop performance optimizations and analyses, and craft and implement compiler techniques for AI workloads and future NVIDIA GPUs.

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, 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 the ability to work in a dynamic, product-oriented team.

Preferred Qualifications

Proficiency in CPU and/or GPU architecture.
CUDA or OpenCL programming experience.
Understanding of deep learning models, algorithms, and frameworks such as PyTorch and JAX.
Experience authoring GPU kernels and analyzing performance using tools such as Nsight Compute.
Experience mentoring early-career engineers and interns.
Experience with new hardware bring-up.

Benefits

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

Applications for this job will be accepted at least until February 27, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.