Registered Nurses (Data labelling and training)

AI Trainer Jobs; United States; Remote; USD 83,000 - 110,000; Part time

Benefits offered by this job

Remote work

Competitive hourly pay

Contractor role

Job summary

AI Trainer Jobs is seeking a credentialed Registered Nurse to review AI-generated nursing outputs. This remote contractor position involves evaluating clinical reasoning, dosing logic, and guideline adherence, with documentation to help close gaps in AI models.

Licensure and clinical experience are required, and applicants should be able to work asynchronously for at least 10 hours weekly. reviewers will use a structured rubric to assess safety and quality, flag patient-safety issues, and

Qualifications

• Active nursing license or board certification required.
• Experience reading patient cases and writing structured assessments.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning citing guidelines, evidence, or standard of care.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against nursing guidelines and standard of care.
• Grade differential reasoning, dosing, and red-flag handling on a structured rubric.
• Flag patient-safety issues with severity tags per clinical-incident taxonomies.
• Capture corrected clinical reasoning so the modeling team can train on it.

Skills

Clinical reasoning

Guideline review

Patient-safety assessment

Structured clinical writing

Nursing

Education

Nursing license/board certification

Job description

Registered Nurses (Data labelling and training) is a remote clinical-review track for evaluating AI outputs that touch nursing. Reviewers grade differential reasoning, dosing logic, and guideline adherence; flag patient-safety issues; and document the corrected clinical reasoning so the modeling team can close the gap.

Category: Medical & Clinical AI · Pay: $60–$80 / hr · Location: Remote — US-eligible · Contractor

Registered Nurses (Data labelling and training) is a remote clinical-review track for evaluating AI outputs that touch nursing.

Role details

About the role

Registered Nurses (Data labelling and training) is a remote clinical-review track for evaluating AI outputs that touch nursing. Reviewers grade differential reasoning, dosing logic, and guideline adherence; flag patient-safety issues; and document the corrected clinical reasoning so the modeling team can close the gap.
Nursing AI is only useful if a credentialed clinician would sign their name to the output. AuraOne uses licensed and credentialed reviewers to set the bar for clinical reasoning, dosing, and guideline adherence in regulated workflows.
Review clinical and biomedical AI outputs. Your safety judgment is the point.

Responsibilities

• Review AI outputs against current nursing clinical guidelines and standard of care for Registered Nurses (Data labelling and training) assignments.
• Grade differential reasoning, dosing, and red-flag handling on a structured rubric.
• Flag patient-safety issues with severity tags that match clinical-incident taxonomies.
• Capture the corrected clinical reasoning so the modeling team can train on it.Track Healthcare review Work model Remote · Independent specialist contractor Compensation $60–$80 / hr Eligible from US

What you should bring

• Active or recent license / board certification in nursing or an adjacent specialty for Registered Nurses (Data labelling and training) work.
• Hands-on clinical experience reading patient cases and writing structured assessments.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that cites guidelines, evidence, or standard of care.
• Reliable async availability for at least 10 hours per week.

Role signals

Example tasks

• Grade a model's differential-diagnosis reasoning on a nursing case and write a 2-3 sentence assessment.
• Flag a dosing miscalculation with the right severity tag and corrected dose.
• Adjudicate a disputed case between two reviewers using current specialty guidelines.
• Audit a 25-case batch for rubric consistency and report drift to the program lead.

Useful experience

• Prior work as a guideline reviewer, peer reviewer, or clinical educator.
• Familiarity with AI-assisted clinical decision support and its failure modes.
• Bilingual clinical experience for non-English patient cases.

Compensation and schedule

$60–$80 / hr
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Clinical reasoning
• Guideline review
• Patient-safety assessment
• Structured clinical writing
• Nursing

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• - 01 Confirm profile and eligibility details.
• - 02 Attach this role deliberately.
• - 03 Receive a human review decision or follow-up.

Placement timing depends on program demand and reviewer confirmation.