Research Scientist - RL Training

[…] is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.

Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

We're looking for a Research Scientist to work on reinforcement learning for training and aligning large language models. This is a foundational research role focused on one of the most consequential open data problems in AI: how to generate the data, reward signals, and training procedures that steer LLM behavior in reliable and generalizable directions — and a core capability that directly differentiates Snorkel's data-as-a-service offering.

You'll work closely with Snorkel's research, engineering, and delivery teams to advance our RL data capabilities — translating research ideas into the preference datasets, reward models, and RL-ready corpora we produce for frontier AI labs, and contributing to a research agenda that is central to Snorkel's long-term differentiation as a provider of bespoke training data.

Research and implement reinforcement learning techniques — including GRPO, RLHF, RLAIF, DPO, and reward modeling — a