Research Engineer / Scientist, Data & Evals
Harvey
- Pay
- $230K to $340K
- a year
- Location
- United States
- Work style
- Remote only
- Job type
- Full time
- Posted
- Oct 30
- 2 days ago
Career path
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About the company
Harvey
Computer software · 51 to 200 employees
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
What you'll do
- 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 usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
What you need
- Experience building data pipelines, ML evaluation systems, or experimentation tooling
- Strong Python skills and ownership of production-quality code
- A rigorous approach to measurement, including statistical reasoning and experimental design
- 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 (preferred)
Key skills
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