We are seeking experienced Registered Nurses with inpatient clinical expertise to contribute to a project focused on improving the accuracy, safety, and reliability of AI systems in healthcare.
In this role, you will apply your nursing judgment and knowledge of inpatient workflows to review clinical documentation, annotate medical records, and evaluate AI-generated clinical outputs. Your expertise will help ensure that clinical information is accurate, complete, and consistent with established standards of care.
Prior AI experience is not required. Your practical nursing experience and ability to assess clinical information are what matter most.
Key Responsibilities
- Review inpatient clinical documentation: Examine nursing notes, progress notes, care plans, medical orders, laboratory results, and discharge summaries for accuracy, completeness, and clinical consistency.
- Annotate medical records: Label, categorize, and structure clinical information according to project guidelines to support high-quality healthcare datasets.
- Evaluate AI-generated clinical outputs: Assess responses and summaries for clinical accuracy, patient safety, appropriateness, and consistency with established standards of care.
- Apply nursing judgment: Use bedside nursing experience to identify clinical inconsistencies, missing information, documentation gaps, and potentially unsafe recommendations.
- Validate inpatient workflows: Assess whether clinical documentation accurately reflects patient care processes, nursing responsibilities, and inpatient treatment pathways.
- Identify documentation discrepancies: Flag conflicting information, ambiguous terminology, incomplete records, and other issues that could affect clinical interpretation.
- Provide structured feedback: Document findings clearly, explain identified errors, and recommend corrections that improve data quality and AI model performance.
- Clarify project requirements: Communicate with project stakeholders to resolve questions about annotation guidelines, documentation standards, and complex clinical cases.
- Review edge cases: Evaluate unusual or complex clinical scenarios and provide feedback to improve annotation guidelines and model understanding.
- Maintain quality standards: Verify annotations and submissions for consistency, accuracy, and adherence to project requirements.
- Meet project deadlines: Manage assigned reviews efficiently while maintaining a high standard of clinical accuracy and attention to detail.
Required Qualifications
- Registered Nurse qualification with the ability to practice as an RN in the United States.
- Strong knowledge of inpatient clinical workflows, nursing documentation, and standards of care.
- Ability to review clinical records and assess the accuracy, completeness, and clinical soundness of medical information.
- Sound nursing judgment and the ability to identify documentation errors, inconsistencies, and potential patient safety concerns.
- Strong written and verbal communication skills.
- Excellent attention to detail and the ability to provide clear, structured feedback.
- Ability to work independently and collaborate effectively with project stakeholders in a remote environment.
Preferred Qualifications
- Broad clinical experience across different inpatient populations rather than experience limited to a single specialty.
- Experience working in an academic medical center, teaching hospital, or large healthcare system with complex patients and documentation workflows.
- Previous medical data annotation experience, particularly with positive performance reviews.
- Familiarity with clinical data quality assurance, medical record review, or AI-generated clinical content evaluation.
- Experience interpreting complex clinical documentation and resolving ambiguous or conflicting information.
Compensation & Engagement
- Compensation: $60–$70 per hour.
- Engagement Type: Contractor.
- Work Arrangement: Fully remote.
- Project Focus: Inpatient clinical documentation review, medical record annotation, nursing judgment, and AI evaluation.