GPU Compiler Intern

Job description

As GPU Compiler Intern, you will develop compiler infrastructure for Python-based GPU programming, including CUTLASS CuTeDSL. You will work on DSL design, MLIR IR design, and compiler optimizations that translate expressive Python programs into high-performance NVIDIA GPU kernels. What you will be doing: Design and implement Python DSL features for GPU kernel authoring, including metaprogramming and IR generation. Develop MLIR dialects, transformation passes, and lowering pipelines that preserve the information needed for effective GPU optimization. Design and optimize GPU kernels, exploring how IR design and compiler transformations affect generated code and performance. Profile, benchmark, and validate compiler and kernel improvements across representative workloads. What we need to see: Currently pursuing or holding a Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Computer Engineering, or a related technical discipline, or equivalent practical experience. Proficiency in Python and C++, with strong debugging and software development skills. Understanding of how Python DSLs work, including metaprogramming, staged execution, and translation into compiler IR. Experience with MLIR, including IR construction, transformation passes, or lowering. Practical experience with GPU programming, preferably CUDA, and knowledge of GPU execution and memory models. Familiarity with performance analysis and optimization, including profiling, memory access patterns, and parallel execution. Experience with CUTLASS, CuTeDSL, Triton, LLVM, or other GPU compiler and kernel development tools is a plus.