Startups · AI

Research Intern, Frontier Speculative Decoding (Winter 2027)

Together AI · San Francisco · On-site

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About Together AI

Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research. Backed by General Catalyst, Kleiner Perkins and NEA.

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. Found on 1752vc Careers, the job board for startup and VC roles.

What they're looking for

  • Currently pursuing a Master's or Ph.D. degree in Computer Science, Electrical Engineering, or a related field
  • Strong knowledge of Machine Learning and Deep Learning fundamentals
  • Hands-on experience training or fine-tuning large models with distributed training frameworks (e.g., Megatron-LM, FSDP)
  • Familiarity with modern model architectures, such as Mixture-of-Experts and hybrid attention
More about this 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.

Speculative decoding research by Together researchers, interns and academic collaborators includes:

  • Speculative...

Read the full posting on Together AI's site ↗

Research

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