Systems Research Engineer Intern - GPU Programming (Summer 2026)
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Role Overview: As a Systems Research Engineer Intern focused on GPU programming, you will develop and optimize GPU-accelerated kernels and algorithms for ML/AI workloads.
You will co-design GPU kernels and model architectures with the modeling and algorithm teams to boost performance and efficiency.
Collaborate with hardware and software teams to contribute to the co-design of efficient GPU architectures and programming models.
Responsibilities include optimizing GPU code for scalability, integrating GPU-accelerated solutions into existing software systems, and staying up-to-date with the latest GPU programming techniques.
Requirements: strong background in GPU programming and parallel computing (e.g., CUDA and/or Triton), knowledge of ML/AI applications and models, and experience with performance profiling and optimization tools.
Internship details: ~12 weeks (Summer 2026) in San Francisco with competitive compensation and housing stipends; dates May 18–Aug 7 or Jun 15–Sep 4.
You will co-design GPU kernels and model architectures with the modeling and algorithm teams to boost performance and efficiency.
Collaborate with hardware and software teams to contribute to the co-design of efficient GPU architectures and programming models.
Responsibilities include optimizing GPU code for scalability, integrating GPU-accelerated solutions into existing software systems, and staying up-to-date with the latest GPU programming techniques.
Requirements: strong background in GPU programming and parallel computing (e.g., CUDA and/or Triton), knowledge of ML/AI applications and models, and experience with performance profiling and optimization tools.
Internship details: ~12 weeks (Summer 2026) in San Francisco with competitive compensation and housing stipends; dates May 18–Aug 7 or Jun 15–Sep 4.
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