Inpatient Nursing Expert - Clinical Evaluator

Mercor; New York (NY); On-site; USD 70,000 - 100,000; Full time

Job summary

Mercor is seeking experienced Adult Inpatient Nurses (RNs) to train and evaluate AI systems used in clinical and healthcare settings. This role leverages frontline nursing expertise to improve AI accuracy, safety, and reliability.

You’ll work on projects requiring deep clinical judgment and the ability to translate bedside documentation into structured feedback for AI models. Strong documentation and communication are essential.

Qualifications

• Active RN license in the U.S. (excluding California).
• Recent adult inpatient bedside experience in non-procedural area.
• Experience within the last 5–10 years reflecting current workflows and documentation practices.
• Ability to perform and document comprehensive nursing assessments.
• Ability to follow annotation guidelines consistently.
• Excellent written communication and responsiveness to feedback.
• Ability to work independently and meet deadlines.

Responsibilities

• Review and evaluate AI-generated clinical outputs based on nursing flowsheet documentation
• Validate accuracy, completeness, and adherence to current documentation standards
• Annotate and structure inpatient nursing assessment data for AI training datasets
• Provide expert feedback on nursing assessments and documentation practices
• Identify gaps, inconsistencies, or risks in AI-generated responses
• Ask clarifying questions when annotation guidance is ambiguous, and contribute to guideline refinement
• Collaborate with technical teams to improve model performance
• Contribute to the development of high-quality clinical benchmarks

Skills

Active RN license

Attention to detail

Excellent written communication

Independent work style

Clinical judgment

Tools

Epic EHR

Annotation tools

Web-based platforms

Job description

We're hiring experienced Adult Inpatient Nurses (RNs) to help train and evaluate AI systems used in clinical and healthcare settings. This role is ideal for nurses who want to apply their frontline experience to improve the accuracy, safety, and reliability of medical AI tools.

You’ll work on projects that require deep clinical judgment, attention to detail, and the ability to translate real-world bedside documentation practices into structured feedback for AI systems.

Key Responsibilities

• Review and evaluate AI-generated clinical outputs based on nursing flowsheet documentation
• Validate accuracy, completeness, and adherence to current documentation standards
• Annotate and structure inpatient nursing assessment data for AI training datasets
• Provide expert feedback on nursing assessments and documentation practices
• Identify gaps, inconsistencies, or risks in AI-generated responses
• Ask clarifying questions when annotation guidance is ambiguous, and contribute to guideline refinement
• Collaborate with technical teams to improve model performance
• Contribute to the development of high-quality clinical benchmarks

Basic Qualifications

• Active RN license (U.S., outside California)
• Recent adult acute care inpatient bedside experience, ideally in a non-procedural area of specialty
• Experience within the last 5–10 years, reflecting familiarity with current workflows and documentation practices (current documentation experience is prioritized over total years of nursing experience)
• Comfortable performing and documenting comprehensive nursing assessments
• Comfortable following detailed annotation guidelines consistently
• Excellent written communication skills and responsiveness to feedback
• Ability to work independently and meet deadlines

Preferred Qualifications

• Epic EHR experience (most common platform, closely aligns with many workflows)
• Comfortable learning new annotation tools and web-based platforms
• Able to navigate transcripts efficiently and use AI-assisted tools appropriately while still verifying outputs
• Experience reviewing charts for quality improvement, utilization review, CDI, or clinical informatics
• Previous annotation, chart abstraction, or healthcare AI experience