GPU Systems Research Intern (CUDA/Triton)

Togetherai; San Francisco (CA); On-site; USD 80,000 - 96,000; Part time

Benefits offered by this job

Housing stipend

Competitive compensation

Job summary

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

You will stay current with the latest GPU programming techniques and contribute to AI infrastructure innovations, aligning with industry-leading engineering practices.

Qualifications

• 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.

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.

Skills

CUDA

Triton

ML/AI models

Profiling tools

Problem-solving

Job description

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

You will stay current with the latest GPU programming techniques and contribute to AI infrastructure innovations, aligning with industry-leading engineering practices.