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Research Engineer / Scientist, Reinforcement Learn

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Research Engineer / Scientist, Reinforcement Learn in UK new

  • London

Responsibilities

  • Own and pursue research to improve model capability on long-horizon legal reasoning and agentic workflows.
  • Design and run post-training experiments using supervised fine-tuning and reinforcement learning on leading open-weight models.
  • Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data.
  • Run and debug large-scale training while addressing divergence, reward hacking, and instability.
  • Build and use rigorous evaluations to track improvements and determine what ships.
  • Design, implement, test, and debug code across the research stack.

Requirements

  • Hands-on experience post-training large language models with supervised fine-tuning, reinforcement learning, and preference optimization.
  • Direct ownership of training runs and results.
  • Deep machine learning fundamentals and experience getting distributed training runs working reliably.
  • Strong Python engineering skills, including production-quality code and end-to-end system ownership.
  • Research experience in reinforcement learning for language models or reward modeling.
  • Ability to move quickly from experiments to shipped improvements.
  • Publications are welcome but not required.

Salary: $230k - $340k/yr

Harvey

Harvey is domain-specific AI for legal and professional services. Adopted by Fortune 500 companies like AT&T, Verizon, Cox, Koch, KKR, Bridgewater, more than 100,000 lawyers across 2,400+ customers in 70 countries and over 75% of AmLaw 100 law firms rely on Harvey to advance legal expertise faste...

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