Real Estate Compliance Reviewer (Contract)

About OpenTrain AI

OpenTrain AI is the #1 platform for building careers in AI training and data labeling. We connect skilled contributors with practical, high-impact projects that teach AI systems to behave correctly and safely.

This role is hired and contracted through OpenTrain AI — you will work directly with our team to label documents and provide the expert judgment that trains an AI compliance reviewer used by residential brokerages.

Why this AI training work matters

AI training (also called annotation or human feedback) is the human expertise behind every reliable AI system. Subject-matter experts label examples, correct model outputs, and set standards so models learn to make correct, defensible decisions.

This project focuses on residential real estate compliance: your reviews will directly shape how the AI evaluates transaction files, helping brokerages stay compliant across U.S. states.

The role

You will review de-identified U.S. residential real estate transaction documents in a web-based labeling tool (OPEN_LABEL), evaluate AI-generated findings, label compliance issues, identify supporting evidence, and write the correct outcome or correction an agent should take.

This is a contract position for contributors with expert-level real estate compliance experience. Work is paid per hour; OpenTrain AI manages contracts and payments.

• Data type: documents (transaction files, agreements, disclosures, addenda, signatures, etc.)
• Label types you will perform: CLASSIFICATION, BOUNDING_BOX, ENTITY_NER_CLASSIFICATION, TEXT_GENERATION, AGENT_EVALUATION, REASONING_VERIFICATION, FACT_CHECKING
• Labeling software: OPEN_LABEL
• Employment type: Contractor

What you'll do day-to-day

Your core responsibilities centre on careful, evidence-based review of de-identified transaction files and the AI’s suggested findings.

• Review purchase and sale agreements, disclosures, addenda, signatures, initials, dates, commission statements, and required brokerage forms
• Evaluate and label AI-generated findings for correctness and completeness
• Pinpoint and cite exact supporting evidence (document name, page, field, or rule)
• Write clear, actionable corrections or outcomes for agents and annotate uncertainty when applicable
• Flag ambiguous cases and provide rationale to help refine model standards and training data

Minimum requirements

We screen for professionals with hands-on experience reviewing U.S. residential transaction files. Please ensure your application demonstrates the items below.

• At least three years of direct experience reviewing residential real estate transaction files (brokerage compliance reviewer, transaction coordinator, managing broker, auditor, compliance manager, or similar)
• Proven experience with purchase and sale agreements, disclosures, addenda, signatures, initials, dates, commissions, and brokerage-required documents
• Familiarity with Washington and/or Oregon forms and brokerage compliance requirements
• Ability to distinguish genuine compliance issues from brokerage preferences and to document that distinction
• Skill in citing the exact document, page, field, or rule that supports a compliance decision
• Ability to write clear, actionable corrections for agents and to flag uncertainty rather than guessing
• Comfort working with de-identified documents inside a web-based labeling tool

How we evaluate applicants

Because this project establishes standards used across states, we require demonstrable judgment and written evidence of prior work.

In your application, be prepared to walk through one real example: describe a compliance issue you identified, the evidence you relied on (document, page, field, or rule), and the correction you recommended.

• Show a short, concrete example from your experience (one-paragraph summary is fine)
• Explain how you would annotate a de-identified transaction file and the specific fields or language you would cite
• Demonstrations of experience with Washington or Oregon forms will be prioritized

Compensation, logistics, and next steps

This is a contractor role paid hourly via OpenTrain AI. Rates for this project range from USD 50–150 per hour, with a typical rate around USD 100 per hour.

Candidates must be based in the United States. OpenTrain AI will provide access to the OPEN_LABEL web tool and training materials; work consists of labeling de-identified documents and providing written judgments.

• Pay type: PAY_PER_HOUR, currency USD, hourlyMin 50, hourlyMax 150, hourlyRate 100
• Location: United States only
• To apply: submit your resume, a short example of a compliance review as described above, and a brief summary of your experience with WA/Oregon forms if applicable