harvey - Research Engineer / Scientist, Reinforcement Learning

London1h ago

In Office EMEA Artificial Intelligence Research Engineer Python Notion

Requirements

• Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. • Deep ML fundamentals and experience getting distributed training runs working reliably. • Strong engineering skills in Python, with production-quality code and end-to-end system ownership. • Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. • We are hiring for this role across multiple levels. • DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.

Responsibilities

• Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. • Design and run post-training experiments across SFT and RL, building on leading open-weight models. • Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. • Run and debug training at scale, addressing divergence, reward hacking, and instability. • Build and use rigorous evals to track improvements and decide what ships. • Design, implement, test, and debug code across our research stack.

Benefits

• At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.