Research Intern, Frontier Speculative Decoding (Summer 2027)
Together AI · San Francisco
Infrastructureonsiteintern$121k–$146k
At a glance
Highlights
- Build draft models that speed up frontier LLMs without changing outputs.
- Train and test drafters at scale against long-context, agentic traffic.
- Co-design training, inference algorithms and serving for faster generation.
What they offer
- housing stipends
Ideal candidate
A Master's or PhD student passionate about efficient LLM inference who loves bridging research and production to make frontier models faster and cheaper to serve.
Requirements
- Currently pursuing a Master's or Ph.D. in Computer Science, Electrical Engineering, or related field
- Strong knowledge of Machine Learning and Deep Learning fundamentals
- Hands-on experience training or fine-tuning large models with distributed training frameworks
- Familiarity with modern model architectures such as Mixture-of-Experts and hybrid attention
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
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