AI Computing Software Intern, GPU Kernel Libraries - 2027

Responsibilities

• Develop high performance operators on NVIDIA GPUs for cuBLAS, TensorRT, cuDNN, cuSparse and cuTensor libraries
• Analyze the performance of various GPU kernels on existing/new architecture, identify bottlenecks and propose creative solutions to improve them
• Design and develop software for kernel authoring and shipping
• Adopt cutting-edge AI technologies in GPU kernel or similar development workflow
• What we need to see
• Pursuing a B.S., M.S., or PhD degree in computer science (or similar)
• Strong programming skills in C/C++ and Python development
• Familiar with GPU programming model and CUDA
• Good understanding about compiler technologies and experience with LLVM and MLIR
• Excellent problem solving skills, good communication and teamwork

Languages