Clinical Law Professor, Clinic Director (AI Legal Reviewer)

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. We connect skilled freelancers with short-term, specialized projects that help shape how modern AI systems behave while letting contributors build a reusable portfolio of verified AI-training experience.

We hire and contract directly for this role. Working with OpenTrain means joining a fast-growing industry where part-time, remote, and flexible engagements are common and where your subject-matter expertise has immediate impact on AI quality.

About AI training and this work

AI training (also called data labeling or human feedback work) is the human side of building intelligent systems: experts review model outputs, rate them, and provide corrections and structured feedback so models learn to reason more accurately. This role focuses on reviewing legal reasoning generated by AI in civil legal-service scenarios.

Your evaluations will feed RLHF-style processes and evaluation ratings that directly improve how legal-assistance models spot issues, apply doctrine, and propose procedural next steps.

The role

OpenTrain is seeking a Clinical Law Professor or Clinic Director to evaluate AI-generated legal analyses and responses for civil legal issues. You will assess issue spotting, legal reasoning, and procedural analysis across housing, family, consumer, elder, disability, and debt matters and provide structured feedback to improve model outputs.

This is a remote, contractor role for approximately 15 hours per week with an estimated project duration of 2 to 3 weeks. Pay is $180 per hour. Candidates must be located in the United States and able to work in English.

• Commitment: ~15 hours/week for 2–3 weeks
• Pay: $180 per hour (contractor)
• Location: Remote — U.S. applicants, English required
• Work type: Part-time contractor; short-term project

What you'll do

Provide expert review and structured assessment of AI-generated legal responses. Your work will combine doctrinal judgment with practical clinic supervision experience to rate accuracy and coach model outputs toward client-ready guidance.

• Review AI-generated legal analyses and responses for accuracy, clarity, and completeness
• Evaluate issue spotting, applicability of legal rules, and procedural recommendations
• Assess civil law scenarios involving housing, family, consumer, elder, disability, and debt topics
• Provide structured feedback and model corrections using provided rubrics and rating tools
• Draw on experience supervising law students and live-client clinics when judging practical adequacy

Requirements

You must meet the stated qualifications and be able to demonstrate past clinic supervision or clinic-directing experience. Do not apply unless you meet these core criteria.

• Juris Doctor (JD) degree
• Current or previous U.S. bar admission
• Experience directing or supervising a law school clinic
• Demonstrated expertise in one or more civil legal practice areas (housing, family, consumer, elder, disability, debt)
• Strong legal writing, evaluation, and assessment-rubric skills
• Experience reviewing AI-generated legal reasoning for accuracy (required)

Helpful background

The project favors candidates with deep clinic teaching and assessment experience. These qualifications make it easier to convert hands-on legal supervision into concise, actionable feedback for models.

• Clinical Professor of Law or Clinic Director experience
• Background running housing, family, consumer, elder, disability, or debt clinics
• Experience developing legal curriculum or assessment rubrics
• Published scholarship, teaching materials, or prior assessment reports (helpful but not required)