Deep Learning Compiler Engineer - CUDA

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 now looking for cuTile Core Compiler Architect in our group! The NVIDIA Architecture group is looking for world class architects and engineers to join and lead our various architecture efforts. A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly looking for ways to improve our GPU architecture and maintain our leadership by developing new parallel programming models, new architectures and new infrastructure that is required to make this successful.

What you'll be doing

• Design and implement the DSL and the core compiler of tile-aware GPU programming model for emerging GPU architectures
• Continuously innovate and iterate on the core architecture of the compiler to consistently optimize performance
• Investigation of next-generation GPU architectures and provide solutions in the DSL and compiler stack
• Performance analysis on emerging AI/LLM workloads and integrate with AI/ML frameworks

What we need to see

• Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)
• 2+ years of relevant work experience
• Excellent C/C++ programming and software engineering skills, ACM background is a plus
• Good fundamental knowledges on computer architecture
• Strong ability in abstracting problems and the methodology in resolving problems
• Strong compiler backgrounds including MLIR/TVM/Triton/LLVM is desired
• Good knowledge of GPU architecture and fast kernel programming skills is a plus
• Knowledge of LLM algorithms or a certain HPC domain is a plus
• Knowledge of multi-GPU distributed communication is a plus
• Excellent oral communication in English is a plus

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/