NVIDIA's invention of the GPU 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, we are increasingly known as “the AI computing company”.
NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning—from LLMs and generative AI to recommendation, vision, and speech. On this team, you’ll build an MLIR-based AI compiler that powers NVIDIA’s inference engine end to end, with a focus on performance, fast builds, low memory use, and Ahead-of-Time and Just-in-Time usability across data center and edge.
What you’ll be doing:
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, and contribute to other general software engineering work.
What we need to see:
Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.
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.
Ways to stand out from the crowd:
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.
A track record of mentoring early career engineers and interns is a bonus
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.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
- Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, related field, or equivalent experience.
- 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 development efforts.
- Strong interpersonal skills and ability to thrive in a fast-moving, product-oriented team.
- 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.
- Track record of mentoring early career engineers and interns.
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.”
