Research Engineer, Data & Evals

Key responsibilities: Develop synthetic data pipelines for training and evaluation of legal reasoning models Design and calibrate evaluations that reflect real legal work, ensuring alignment with expert judgment Collaborate with researchers to analyze model failures and improve training based on customer feedbackRequired qualificationsExperience in building data pipelines, ML evaluation systems, or experimentation tooling with strong Python skills Understanding of statistical reasoning and experimental design for accurate measurement Ability to convert ambiguous goals into structured datasets and measurable criteria Familiarity with synthetic data, LLM evaluations, or automated raters is a plus Strong background in data and measurement engineering related to ML model development