Research Intern (Summer 2026)
About the role
AI research center for retrieval. SID trains AI that can retrieve and reason over any data source. Backed by YC and top investors. In-person internship in San Francisco.
Responsibilities
- Post-train reasoning into LLMs with GRPO and SFT.
- Design and iterate RL training environments for retrieval – unstructured, structured, web.
- Run small and large model experiments – yolo runs encouraged.
- Work on next-generation vision-first embedding models.
Qualifications
- Not afraid of formulas – a technical major is an indicator of this (but isn't the only one).
- Thinks they can learn anything in 2 weeks, but isn't arrogant about it.
- Prefers .py to .tex
- Familiar with RL pipelines for language models
- Comfortable with torchrun/accelerate/multi-node training.
- Clever about getting the data needed – or synthetically generating it.
- Finds easy solutions to hard problems, but willing to dive into PyTorch or CUDA.
- Familiar with 'You and Your Research.' Understands what it takes to do significant work.
- Must articulate ideas well, including writing docs and technical reports and possibly participating in podcasts.
Skills
Benefits
- Work on frontier methods that scale.
- Everyone on the team can code – potential for future changes.
About SID
Serverless RAG to connect AI to company, industry, or person-specific…
We make it easy for developers to connect data to their LLM apps. Instead of spending months on integrations and retrieval pipelines, Reworkd's AgentGPT added our button in an afternoon and let thousands of people connect their Notion, email and Drive instantly. Every single AI company is building data retrieval. Currently, they're doing this from scratch – we don't think they should have to. Just like OpenAI made working with LLMs as simple as an API call, SID makes it easy for every AI company to access data the same way.
More open roles at SID
- Research Engineer5mo agoHybrid (San Francisco, CA)