Senior AI Compiler Engineer, MLIR

Reposted 10 Hours Ago
Be an Early Applicant
3 Locations
In-Office or Remote
152K-242K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and implement MLIR-based graph representations, dialects, and compiler optimizations for GPU inference. Partner with framework and hardware teams, define APIs, perform performance analysis, and generate high-performance kernels for neural networks.
Summary Generated by Built In

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 28, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Top Skills

C
C++
Cuda
Gpu Kernel Generation
Jax
Llvm
Mlir
Opencl
Python
PyTorch
Xla
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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