Use pediatric inpatient nursing expertise to evaluate clinical AI outputs, annotate documentation, and improve healthcare models. This part-time contractor role pays $55 to $65 per hour and requires an active U.S. RN license outside California.
Medical & Health
Remote Hourly · $55–$65/hr
$55–$65/hr
Compensation
1 country
Eligibility
Entry
Experience
Sep 2, 2026
Posted
Open to applicants in
United States
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Contractor and part-time opportunity
United States-based applicants only, excluding California
English-language work
20+ hours per week
$55 to $65 per hour
About AI Training Work
AI training is the human side of building artificial intelligence. Specialists review examples, assess model responses, and prepare structured data so AI systems can become more accurate, reliable, and useful.
In healthcare, experienced professionals help evaluate clinical outputs against trusted documentation and professional standards. Your judgment can help shape how medical AI systems handle complex nursing information.
Apply real-world expertise to improve AI systems
Combine professional judgment with structured data work
Support clinical benchmarks and safer model performance
Build experience in a fast-growing technology field
The Role
OpenTrain is recruiting experienced pediatric inpatient nurses and registered nurses to evaluate AI systems used in clinical and healthcare settings. You will assess AI-generated clinical outputs against nursing flowsheet documentation and current documentation standards.
The work combines pediatric bedside expertise, clinical documentation review, structured annotation, and careful evaluation of AI-generated content. The listing is classified as entry level, but applicants must meet the specified professional licensing and pediatric inpatient experience requirements.
You will review, classify, and evaluate clinical information with close attention to accuracy, completeness, safety, and reliability. You will also help create high-quality datasets and benchmarks for healthcare AI systems.
The role requires consistent application of detailed guidance while using independent clinical judgment when documentation or instructions are ambiguous.
Review AI-generated clinical outputs against nursing flowsheet documentation
Annotate and structure inpatient pediatric nursing assessment data
Identify gaps, inconsistencies, and potential risks
Provide expert feedback on nursing assessments and documentation practices
Ask clarifying questions when annotation guidance is ambiguous
Contribute to refining annotation guidelines
Collaborate with technical teams to improve model performance
Support the development of high-quality clinical benchmarks
Required Qualifications
You must have an active registered nurse license in the United States, excluding California, as well as recent pediatric acute-care inpatient bedside experience. Experience in a non-procedural inpatient unit is preferred.
You should be able to perform and document comprehensive pediatric nursing assessments, follow detailed annotation guidance consistently, and make careful clinical judgments about AI-generated clinical content.
Ability to document comprehensive pediatric nursing assessments
Ability to evaluate clinical AI outputs for accuracy, completeness, and risk
Ability to follow detailed annotation guidance
Ability to explain decisions involving edge cases
Strong written communication and responsiveness to feedback
Independent work habits and reliability in meeting deadlines
Helpful Experience
The following experience is not listed as required, but may help you contribute effectively to this project. Familiarity with clinical documentation workflows and AI-assisted review can be especially useful when evaluating nuanced nursing records.
Epic EHR workflows
Chart review for quality improvement
Utilization review
Clinical documentation improvement
Clinical informatics
Previous annotation or chart abstraction
Healthcare AI experience
Web-based annotation tools
Efficient transcript navigation
Verification of AI-assisted outputs
Why Work With OpenTrain
AI training and data-labeling work is a flexible way to apply specialized knowledge to cutting-edge technology. Many projects are remote and part time, allowing contributors to fit work around other responsibilities while developing experience in a growing industry.
OpenTrain helps you manage opportunities in one place, show credible experience through your profile, and grow AI training and data-labeling work into a durable professional portfolio.
Use your pediatric nursing expertise beyond traditional clinical workflows
Contribute directly to the development of medical AI tools
Work part time for 20 or more hours per week
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