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AI Computing Software Intern, GPU Kernel Libraries - 2027

NVIDIA· Intern
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Shanghai, China, Beijing, ChinainternPosted 4w ago

About the role

Compute/DL Architecture Performance Optimization Intern role focused on exploring computer architectures for deep learning, optimizing GPU kernel performance, and delivering scalable modular infrastructure for NVIDIA software libraries used in training and inference.

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

Qualifications

  • 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

Skills

Required:C/C++ programmingPythonCUDA
Nice to have:LLVMMLIR
Last updated Sep 25, 2026. Interested? Apply on the company site.

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