Senior DL Compiler Engineer -CUDA Tile

Nvidia
US, CA, Santa Clara / US, TX, Austin / US, WA, Remote2026-06-16remote_local

About the job

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 hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification and other areas. Come join us to work with a top-notch team and have broad impact across the entire deep learning community.

Responsibilities

Design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the performance of tile-based kernels to ensure they execute efficiently across multiple generations of NVIDIA GPU architectures. Define public APIs, craft and implement compiler and optimization techniques, performance optimization, and other general software engineering work.

Qualifications

Minimum

Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering or a related field (or equivalent experience)

3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design.

Ability to work independently, define project goals and scope, and lead your own development effort.

Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.

Preferred

Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.

Experience with the following technologies: MLIR, LLVM, XLA, TVM and deep learning models and algorithms.