The work
You will review transformed datasets and documents used in AI training. Your job is to check whether personal information has been properly redacted or anonymized and whether privacy standards are applied consistently.
You will record issues using the provided tools and templates, then give clear feedback that helps improve the quality and reliability of the data.
- Spot-check transformed datasets for missed or incorrectly handled personally identifiable information.
- Review documents in detail for consistent use of data privacy standards.
- Identify subtle privacy issues and explain what needs to be corrected.
- Record discrepancies and observations clearly and accurately.
- Handle sensitive information carefully during every review.
What it pays and takes
This is a contractor, part-time opportunity listed at entry level. The work requires professional fluency in English and strong experience with privacy, compliance, or legal document review.
- $31 to $60 per hour.
- Open to candidates in the countries listed for this role across the Americas, Europe, Asia, Africa, and the Middle East.
- Professional fluency in English.
- In-depth knowledge of personally identifiable information and data privacy regulations.
- Experience reviewing legal or compliance-related documents and checking whether requirements have been met.
- Strong analytical judgment, close attention to detail, and clear written communication.
- Experience working with sensitive data in high-stakes environments.
- Relevant backgrounds include paralegal work, eDiscovery, privacy analysis, information governance, compliance management, or legal document review leadership.
- Experience in contract review, quality assurance, litigation support, or managed legal services is also relevant.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that learn from examples, including reviewing documents and checking whether data is accurate, safe, and consistently labeled. People with privacy, legal, and compliance experience are paid for the judgment needed to review sensitive material and improve these datasets.