Registered Nurse Clinical Documentation Reviewer

You will review and annotate inpatient clinical documentation, then assess AI-generated clinical responses. Your work will help improve the accuracy, safety, completeness, and appropriateness of AI systems used with clinical content.

• Review nursing notes, progress notes, care plans, orders, lab results, and discharge summaries.
• Evaluate AI-generated clinical responses for accuracy, patient safety, appropriateness, and completeness.
• Use inpatient workflows, bedside nursing practice, documentation standards, and standards of care to validate and improve datasets.
• Identify unclear or incomplete documentation and communicate with stakeholders to resolve ambiguities.
• Give detailed feedback on guidelines and edge cases to improve workflows and model understanding.

This is remote contractor work for professionals based in the United States. The role is part time, and previous AI experience is not required.

• Pay: $60 to $70 USD per hour.
• Location: Open to candidates based in the United States.
• Professional background: Current or recent inpatient bedside Registered Nurse experience.
• Practice eligibility: Eligible to practice as a Registered Nurse in the United States.
• Clinical experience: Broad exposure across inpatient populations, rather than experience limited to one narrow specialty.
• Skills: Strong written and verbal communication, careful attention to clarity and detail, and consistent judgment about safety, completeness, and appropriateness.
• Helpful background: Experience at an academic medical center or large health system, especially with complex patients, varied inpatient workflows, and detailed documentation.
• Helpful background: Previous annotation experience with positive performance reviews.

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.

AI training is the human work behind systems that learn from examples, including reviewing documents and rating model responses. Experienced professionals are paid for applying their subject knowledge and judgment to make those examples accurate and useful.

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