AI Compiler Intern, CUDA Tile IR - Summer 2027

Job description

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 an inclusive, 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 now hiring deep learning compiler engineering interns to work on CUDA Tile IR! 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. CUDA Tile IR is a new and exciting way to program those GPUs. Come join us to work with an outstanding team and make an impact across the entire deep learning community. What you'll be doing: Improve the performance and expressivity of CUDA Tile IR. Analyze deep learning networks and developing compiler optimization algorithms, adding new constructs to the language to better enable various workloads, and expanding support to new hardware generations. Collaborate with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. What we need to see: Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering, Electrical Engineering, Computer Science, or a similar field Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design. Ways to stand out from the crowd: Experience with the following technologies: MLIR, LLVM, XLA, deep learning models and algorithms, and deep learning framework design. History of contributions to open-source projects. Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/