Senior Compiler Engineer Infrastructure

About the role

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. 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.

What you will be doing:

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

What we need to see:

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 from the crowd:

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

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until August 14, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Posting text as published by Nvidia.

The evidence behind this listing

Workplace

Remote Matched in posting text

Seniority

senior From the job title

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Not established

Location as listed

US, CA, Santa Clara; US, TX, Austin; US, TX, Remote; US, WA, Remote; US, CA, Remote; US, WA, Redmond

Pay and work authorization

Stated pay

$152k–241.5k/yr AI reading of the posting

Visa sponsorship

Not stated

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