Pediatric RN: AI Data Annotation & Clinical Feedback

Obsidian; New York (NY); On-site; USD 90,000 - 120,000; Full time

Job summary

Obsidian is seeking experienced Pediatric Inpatient RNs to train and evaluate AI systems used in clinical care. You will translate bedside documentation into structured feedback to improve AI accuracy and safety for pediatric patients.

Ideal candidates have an active U.S. RN license, recent pediatric inpatient bedside experience, and the ability to follow annotation guidelines with strong written communication.

Qualifications

• Active RN license (U.S., outside California).
• Recent pediatric acute care inpatient bedside experience; inpatient bedside role in past 10 years prioritized.
• Comfortable documenting comprehensive pediatric nursing assessments.
• Comfortable following detailed annotation guidelines consistently.
• Excellent written communication skills 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 pediatric 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

Pediatric nursing

RN license

Clinical judgment

Annotation guidelines

Written communication

Independent work

Attention to detail

Job description

Obsidian is seeking experienced Pediatric Inpatient RNs to train and evaluate AI systems used in clinical care. You will translate bedside documentation into structured feedback to improve AI accuracy and safety for pediatric patients.

Ideal candidates have an active U.S. RN license, recent pediatric inpatient bedside experience, and the ability to follow annotation guidelines with strong written communication.