Deep Learning Compiler Engineer

About the role

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 Tensor IR & 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. What you'll be doing: In this role, you will work on CUDA Tile and TensorIR compiler technologies for NVIDIA GPUs. CUDA Tile is a new tile-based programming model that shipped with CUDA 13.1, and TensorIR is an open-source compiler infrastructure project that uses CUDA Tile to generate high-performance GPU kernels. You will 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. The scope of these efforts includes defining public APIs, crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work. What we need to see: 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. Ways to stand out from the crowd: 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. 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 other objective job-related factors. The expected base salary range for this position 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 November 3, 2026. 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. #deeplearning NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.

Posted Oct 29, 2026