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Together AITogether AISan Francisco, CA

Systems Research Engineer Intern - GPU Programming

Intern developing and optimizing GPU-accelerated kernels for ML/AI applications. Requires strong GPU programming background (CUDA/Triton) and knowledge of performance optimization.

121k – 131k/yr
On-siteEntry levelML Engineering

About the role

Responsibilities

  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies

Requirements

  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills

Internship Program Details

  • Fall internship program spans 12 to 16 weeks (September 14th to December 18th)
  • Opportunity to work with industry-leading engineers building a cloud from the ground up
  • Possibility to contribute to influential open source projects

Compensation

  • Estimated US hourly rate: $58 to $63
  • Competitive compensation, housing stipends, and other competitive benefits

Skills

CUDATritonGpu ProgrammingParallel ComputingPerformance ProfilingMl/Ai ApplicationsOptimization Tools

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