GPU Systems Research Intern – High-Perf ML Kernels

Together AI; San Francisco (CA); On-site; USD 80,000 - 87,000; Full time

Benefits offered by this job

Housing stipend

Job summary

Together AI, the AI Native Cloud, is seeking a Systems Research Engineer Intern specialized in GPU programming. You will develop and optimize GPU-accelerated kernels and algorithms for ML/AI applications, co-design GPU kernels and model architecture, and collaborate with hardware and software teams to advance efficient GPU programming models.

The internship runs 12 to 14 weeks with dates May 17–Aug 6 or Jun 14–Sept 3.

Qualifications

• Strong background in GPU programming and parallel computing (CUDA/Triton).
• Knowledge of ML/AI models and applications.
• Experience with performance profiling/optimization tools for GPUs.
• Excellent problem-solving and analytical skills.

Responsibilities

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

Skills

GPU programming

Parallel computing

ML/AI knowledge

Tools

CUDA

Triton

Profiling tools

Job description

Together AI, the AI Native Cloud, is seeking a Systems Research Engineer Intern specialized in GPU programming. You will develop and optimize GPU-accelerated kernels and algorithms for ML/AI applications, co-design GPU kernels and model architecture, and collaborate with hardware and software teams to advance efficient GPU programming models.

The internship runs 12 to 14 weeks with dates May 17–Aug 6 or Jun 14–Sept 3.