Senior AI Compiler Engineer, Algorithms and Code-Generation

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 looking for an AI & Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning & AI Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AI, recommendation systems, image classification, speech recognition, etc. With the rapid advancement of AI, our DLC has been the backbone of NVIDIA’s inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Time and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.

What you'll be doing:

- Analyzing deep learning networks and developing compiler optimization algorithms.

- Strong programming skills in CUDA including analyzing and debugging performance bottlenecks on GPUs

- Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs.

What we need to see:

- Bachelor’s, master’s or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience.

- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.

- Experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton, etc.).

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

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

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

Ways to stand out from the crowd:

- Proficient in CPU and/or GPU architecture especially modern Nvidia GPUs like Hopper and Blackwell

- Understanding of deep learning models, algorithms, and frameworks, such as PyTorch, JAX.

- GPU kernel authoring and performance analysis using tools such as Nsight Compute.