M&A Redlining Attorney, 2+ Years Law Firm

The work

You will use practical judgment from corporate and M&A transactions to help train and evaluate legal AI models. The work includes simulated negotiations, contract redlining, and structured reviews of AI-generated legal responses.

You will turn complex commercial and legal decisions into clear feedback that supports reliable contract review standards.

• Review corporate and M&A contract scenarios, including asset purchase agreements and stock purchase agreements.
• Perform simulated contract negotiations and redlining exercises.
• Evaluate AI responses for accuracy, risk identification, and legal judgment.
• Create objective evaluation frameworks and grading criteria for contract-related model performance.
• Work with product and research teams to improve data, guidelines, and legal AI review practices.

What it pays and takes

This is a remote, part-time contractor role. English fluency is required, and the role is open to candidates in the countries specified for this opportunity.

• Pay: $90 to $130 per hour equivalent, paid per task that meets project specifications.
• Education: J.D. from an ABA-accredited law school.
• Licensing: Active bar admission in at least one U.S. jurisdiction.
• Experience: At least two years in the M&A department of a corporate law firm.
• Skills: Contract interpretation, risk analysis, strong written and verbal communication, structured legal reasoning, and close attention to detail.
• Helpful background: Experience with private equity, AI, legal technology, training initiatives, or cross-disciplinary product and research teams.

How it works

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

About AI training work

AI training is the human work behind systems that can understand and generate language. Legal specialists review examples, judge model responses, and explain what accurate and useful answers should look like, helping improve how these systems handle specialized work.