Systems Research Engineer Intern - GPU Programming (Winter 2027)
Together AI · San Francisco
CHECKED 3H AGO
Infrastructureonsiteintern$121k–$146k
At a glance
Highlights
- Develop and optimize GPU-accelerated kernels for ML/AI applications.
- Co-design GPU kernels and model architecture for faster AI systems.
- Collaborate with hardware and software teams on GPU architecture design.
What they offer
- housing stipends
- competitive benefits
Ideal candidate
A curious systems thinker passionate about GPU performance and AI efficiency who thrives collaborating across research and engineering to push ML infrastructure forward.
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