Research Engineer / Scientist, Data & Evals

Highlights

• Build synthetic data pipelines powering post-training for legal AI agents.
• Own capability benchmarks like Legal Agent Benchmark tracking real workflows.
• Turn expert feedback and product usage into training signals and rewards.

What they offer

• Equity
• Bonus

Ideal candidate

A rigorous, hands-on research engineer who obsesses over measurement and data quality and loves turning ambiguous expert judgment into clear signals that drive real model improvements.

Requirements

• Experience building data pipelines, ML evaluation systems, or experimentation tooling with strong Python and production-quality code ownership
• Rigorous approach to measurement including statistical reasoning and experimental design
• Ability to translate ambiguous goals and expert judgment into structured datasets, rubrics, and measurable criteria
• Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus