GPU Compiler Intern

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.