Research Engineer / Scientist, Data & Evals

Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.

Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.

Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.

Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.

Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.

A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.

The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.

Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model…