Research Engineer / Scientist, Data & Evals

Highlights

• Build synthetic data pipelines powering post-training for legal AI agents.
• Own evaluations and benchmarks tracking real legal workflows and quality.
• Turn expert feedback into training signals guiding model improvements.

What they offer

• Equity
• Bonus

Ideal candidate

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

Requirements

• Experience building data pipelines, ML evaluation systems, or experimentation tooling with strong Python skills
• Ownership of production-quality code with rigorous approach to measurement, 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
• Strong data and measurement engineering experience close to ML model development