Systems Research Engineer Intern - GPU Programming (Summer 2027)
Together AI · San Francisco
CHECKED 1H AGO
Infrastructureonsiteintern$121k–$146k
At a glance
Highlights
- Develop and optimize GPU-accelerated kernels for ML/AI applications.
- Co-design GPU kernels and model architectures to boost AI efficiency.
- Collaborate across hardware and software teams on AI infrastructure.
What they offer
- housing stipends
- competitive benefits
Ideal candidate
A curious systems researcher passionate about performance and parallel computing who loves collaborating with model and hardware teams to make AI faster and more efficient.
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
Lab profile
About Together AI
AI-native cloud for training and inference on large-scale GPU infrastructure for AI apps and agents.
What they build
- AI-native cloud platform
- GPU clusters for training and inference
- Platform for AI applications and agents
Known for
- Operating large-scale GPU fleets
- Automated infrastructure at massive scale
- Multi-site data center deployment
Key facts
- Over 1M developers
- Operates one of the world's largest GPU fleets
- Infrastructure managing tens of thousands of GPUs