# Research Intern, Frontier Speculative Decoding (Winter 2027) at Together AI

- Company: Together AI
- Status: Open
- Workplace: On-site
- Location: San Francisco
- Level: Junior
- Discipline: AI & ML
- Employment: Internship
- Posted: 2026-10-16
- Skills: DeepSeek, Kimi, GLM
- Apply: https://job-boards.greenhouse.io/togetherai/jobs/5267197007

## Description

About the Role 
 The Speculative Decoding team at Together AI builds the draft models and algorithms that let large language models generate faster without changing their outputs. Our speculators run in production on frontier open models such as DeepSeek, Kimi and GLM. Our work sits at the intersection of model training, inference algorithms and serving systems, and we co-design all three to lower the cost and latency of generation. 
 As a research intern, you will dive into open questions in speculative decoding: new drafter architectures and verification schemes, knowledge distillation and training recipes that align draft and target models, and drafters that adapt as traffic shifts. You will train and fine-tune draft models at scale on dedicated GPU clusters, and test your ideas against realistic serving workloads, including long-context and agentic traffic. 
 Projects aim to answer important research questions in speculative decoding, enabling faster generation on frontier models, drafters that keep pace with changing workloads, and robust, reproducible evaluation under real traffic. 
 Past Research 
 Speculative decoding research by Together researchers, interns and academic collaborators includes: 
• Speculative Speculative Decoding (ICLR 2026) 
• When RL Meets Adaptive Speculative Training: A Unified Training-Serving System (ICML 2026) 
• Beat the Long Tail: Distribution-Aware Speculative Decoding for RL Training (MLSys 2026) 
 Responsibilities 
• Research and prototype new efficient speculative decoding algorithms and draft model architectures 
• Train, fine-tune an

More Together AI roles: https://deviantjobs.com/companies/together-ai