Research Engineer, Data & Evals

Job Summary

Building synthetic data pipelines and evaluation systems, the full-time Research Engineer, Data & Evals will design and maintain benchmarks for legal workflows while collaborating with legal experts to enhance model performance in a remote environment.

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 feedback

Required qualifications

• Experience 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