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:
Recent graduate of a B.S. or M.S in Computer Science, Computer Engineering, or related field (or equivalent experience)
Experience with open-source compiler frameworks
Excellent hands-on C++ programming skills
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 108,000 USD - 178,250 USD for Level 1, and 124,000 USD - 195,500 USD for Level 2.You will also be eligible for equity and benefits.
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.Skills Required
- Recent graduate with B.S. or M.S. in Computer Science, Computer Engineering, or related field (or equivalent experience)
- Experience with open-source compiler frameworks (e.g., LLVM, Clang, MLIR)
- Excellent hands-on C++ programming skills
- Experience working with large-scale, long-lived codebases, including refactoring and restructuring
- Solid understanding of compiler internals including IRs, passes, build systems, and toolchains
- Familiarity with source-control-heavy workflows (downstream vs upstream repos, patch queues, rebasing strategies)
- Strong software engineering fundamentals with emphasis on robust, maintainable developer infrastructure
- Good communication and documentation skills; ability to collaborate across teams and time zones
- 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
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
