Research Engineer – Post-Training

Harvey

Research Engineer focusing on post-training efforts to improve AI models for legal work at Harvey. Collaborating with teams on research projects and experiments to enhance product effectiveness.

Posted 6/27/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $231,000 - $340,000 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Drive post-training experiments, pushing agent performance while navigating the Pareto frontier of cost, latency, security, and governance.
Optimize agent harnesses, including domain-specific skills, tools, subagents, retrieval strategies, and validation loops that improve quality on long-horizon legal work.
Design and develop grading and reward systems that are reliable enough for evaluation, efficient enough for iteration, and strict enough for high-stakes legal work.
Study agent behavior, identifying patterns that correlate with successful work product, and converting those findings into training data, evals, or harness changes.
Work with Harvey researchers and external research partners to define experiments, evaluate methodology, review results, and keep projects moving toward concrete model improvements.

Requirements

What you’ll need

Hands-on experience with post-training or model-training work, such as SFT, preference optimization, RLHF/RLAIF, reward modeling, distillation, or adapting open-weight models to specialized domains.
Strong judgment about model behavior: you can read traces, inspect outputs, identify failure modes, and reason about whether a metric is measuring the thing that matters.
Strong Python and research-engineering ability. You can write clean code, debug experiments, and build the simple but reliable systems needed to make research move faster.
Ability to self-manage ambiguous applied research projects and communicate clearly with researchers, engineers, product teams, domain experts, and external partners.

Benefits

Comp & perks

Comprehensive health, dental and vision coverage
Retirement benefits (401k match up to 4%)
Flexible PTO
Equity participation
Bonus eligibility

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

post-trainingmodel-trainingSFTpreference optimizationRLHFRLAIFreward modelingdistillationPythonresearch-engineering

Soft Skills

strong judgmentself-managementclear communication