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 seeking top-tier AI Compiler Engineers to drive innovation within our world-class compiler organization. In this role, you will push the boundaries of what is possible in AI performance and help build the technology that powers the next generation of computing. Join us and make a tangible impact on a global scale.
What you’ll be doing:
Drive technical innovation: Participating in hands-on development focusing on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs.
Advance the state-of-the-art: Solve complex compilation problems for AI workloads (both inference and training) and successfully transition these breakthroughs into enterprise and consumer products.
Collaborate on hardware/software co-design: Partner with leading experts across our software, hardware, and research divisions to architect and co-design future silicon.
Scale AI to the datacenter: Participating in the advancement and optimization of datacenter-scale AI workload deployments.
What we need to see:
BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). A PhD is strongly preferred.
Experience specializing in compiler optimizations, synthesis, and placement.
MLIR Knowledge: Demonstrated, hands-on experience working with MLIR.
Programming Excellence: Exceptional C/C++ and Python programming and software design skills, including rigorous debugging, performance analysis, and test design.
Team Dynamics: Strong communication and interpersonal skills, with the ability to collaborate effectively in a dynamic, fast-paced, and product-oriented environment.
Ways to stand out from the crowd:
Hardware Implementation: Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures.
LLM Knowledge: Deep understanding of Large Language Model (LLM) inference and its profound implications on computer architecture.
Architecture & Design: Demonstrated understanding in the designing and architecting of comprehensive compiler frameworks from the ground up.
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 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
- BS or MS in Computer Science, Computer Engineering, or related field (or equivalent experience)
- PhD in relevant field
- Experience specializing in compiler optimizations, synthesis, and placement
- Hands-on experience working with MLIR
- Exceptional C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design
- Strong communication and interpersonal skills
- Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures
- Deep understanding of LLM inference and compiler framework architecture and design
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.”
