GPU Systems Research Intern: High-Performance ML Kernels

Together Computer Inc; 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 in San Francisco is seeking a Systems Research Engineer Intern focused on GPU programming to develop and optimize GPU-accelerated kernels for ML/AI applications. You will co-design kernels and model architectures with the modeling team to boost performance and efficiency of our AI systems.

Collaborating with hardware and software teams, you will stay current with GPU programming advances and contribute to efficient GPU architectures and programming models.

Qualifications

• Background in GPU programming and parallel computing (CUDA/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 for performance and scalability.
• Collaborate with cross-functional teams to integrate GPU-accelerated solutions into software.
• Stay up-to-date with advancements in GPU programming techniques and technologies.

Skills

GPU programming

Parallel computing

Analytical skills

Tools

CUDA

Triton

Profiling tools

Job description

Together AI in San Francisco is seeking a Systems Research Engineer Intern focused on GPU programming to develop and optimize GPU-accelerated kernels for ML/AI applications. You will co-design kernels and model architectures with the modeling team to boost performance and efficiency of our AI systems.

Collaborating with hardware and software teams, you will stay current with GPU programming advances and contribute to efficient GPU architectures and programming models.