Senior Compiler Engineer Infrastructure

at Nvidia

📍 Santa Clara, United States

USD 152,000-241,500 per year

SENIOR

✅ On-site

Used Tools & Technologies

Machine Learning

Required Skills & Competences
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.

Hiring @ 4 Communication @ 4 Parallel Programming @ 4 CUDA @ 4 GPU @ 4 Deep Learning @ 3 AI @ 4 LLVM @ 4

Details

Come join the team and see how you can make a lasting impact on the world. We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler Team, with a primary focus on aligning NVIDIA’s compiler codebases with open-source ecosystems and improving developer productivity at scale. This role sits at the intersection of open-source compiler development, internal compiler infrastructure, and developer experience. You will play a central role in reconciling downstream compiler repositories with upstream open-source projects such as LLVM, Clang, and MLIR, while building the tooling, workflows, and infrastructure that enable compiler engineers across NVIDIA to move faster and with higher confidence.

Our compiler organization makes its mark on every GPU NVIDIA produces. By improving how our internal compiler stacks align with open source and by modernizing the tools our developers rely on, you will help ensure that NVIDIA continues to lead in scalable, maintainable, and community-driven compiler technology. If you are passionate about open-source stewardship, large-scale codebase alignment, and using modern tooling (including AI-assisted workflows) to improve developer velocity, we would love to hear from you.

Responsibilities

Reconcile and synchronize downstream compiler codebases with open-source repositories, including restructuring, refactoring, and upstreaming internal changes where appropriate.
Lead efforts to restructure, merge, or retire internal code to reduce divergence from upstream open-source projects.
Design and build infrastructure, tooling, and developer workflows that improve productivity, correctness, and maintainability for internal compiler engineers.
Develop automation and developer tools to aid in rebasing, patch management, validation, and large-scale refactoring.
Explore and apply AI-assisted tools to improve developer workflows, including code navigation, change analysis, refactoring assistance, testing, and review efficiency.
Partner with compiler developers, architecture teams, and CI/test infrastructure teams to ensure changes scale across geographically distributed organizations.
Serve as a technical bridge between internal compiler development and open-source ecosystems, helping shape long-term alignment strategies.

Requirements

B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent experience).
Experience with open-source compiler frameworks.
Excellent hands-on C++ programming skills.
3+ years experience working with large-scale, long-lived codebases, including refactoring and restructuring efforts.
Solid understanding of compiler internals, including IRs, passes, build systems, and toolchains.
Familiarity with source-control–heavy workflows (e.g., downstream vs. upstream repos, patch queues, rebasing strategies).
Strong software engineering fundamentals with an emphasis on robust, maintainable developer infrastructure.
Good communication and documentation skills; ability to collaborate across teams and time zones.

Ways to Stand Out

Direct experience reconciling or maintaining downstream forks of open-source projects.
Experience building developer productivity tools, CI infrastructure, or large-scale automation.
Practical experience applying AI or ML-based tools to improve engineering workflows.
Background in GPU programming, CUDA, or parallel programming models.
Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs.

Compensation and Benefits

Base salary range: 152,000 USD - 241,500 USD (actual base salary determined by location, experience, and comparable positions).
Eligible for equity and benefits (link to NVIDIA benefits referenced in posting).

Additional Information

Applications for this job will be accepted at least until May 11, 2026.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer and emphasizes diversity and non-discrimination in hiring and promotion practices.