Data & Evaluation Engineer, Legal AI

Harvey; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Harvey is transforming how legal and professional services operate through AI-driven data evaluation and benchmarking. As a Member of Technical Staff, Data Evals in Harvey Research, you will build the data and measurement systems powering post-training and agent capabilities.

You will own synthetic data pipelines, evaluation design, and the feedback loop from domain experts into training signals. You’ll join a small, high-bar team of hands-on engineers and researchers, collaborating with legal

Qualifications

• Build synthetic data pipelines for training and evaluation samples in legal reasoning.
• Design evaluations and verifiers reflecting real legal work and calibrate against expert judgment.
• Collaborate with researchers and legal experts to translate model failures into improvements.

Responsibilities

• 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.
• Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
• Close the loop from product

Skills

Data pipelines

ML evaluation design

Cross-functional collaboration

Job description

Harvey is transforming how legal and professional services operate through AI-driven data evaluation and benchmarking. As a Member of Technical Staff, Data Evals in Harvey Research, you will build the data and measurement systems powering post-training and agent capabilities.

You will own synthetic data pipelines, evaluation design, and the feedback loop from domain experts into training signals. You’ll join a small, high-bar team of hands-on engineers and researchers, collaborating with legal