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Internship Medical Data Annotation Jobs (NOW HIRING)

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

Use hands-on collection and annotation work to surface tooling gaps and drive the tooling roadmap above. Team Management & Documentation - 25% * Manage and schedule data collection interns and ...

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

Use hands-on collection and annotation work to surface tooling gaps and drive the tooling roadmap above. Team Management & Documentation - 25% * Manage and schedule data collection interns and ...

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

Use hands-on collection and annotation work to surface tooling gaps and drive the tooling roadmap above. Team Management & Documentation -- 25% * Manage and schedule data collection interns and ...

Tread Athletics

Data Support Internship

Data Support Internship Location: Remote Hours: Part-time Please note that this a remote ... Ability to hit preset frame annotation quota each week (estimation of ~10-15 hours of work per week)

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Internship Medical Data Annotation information

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How much do internship medical data annotation jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for internship medical data annotation in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Medical Data Annotation vs Medical Data Labeling Specialist?

AspectInternship Medical Data AnnotationMedical Data Labeling Specialist
CredentialsTypically students or entry-level with basic knowledgeRelevant certifications or experience in data annotation
Work EnvironmentInternship programs, often in healthcare or tech companiesFull-time or part-time roles in healthcare tech firms
Industry UsageUsed for training and educational purposes, entry-level projectsOperational roles focusing on data accuracy and labeling

Internship Medical Data Annotation roles are usually entry-level positions designed for students or newcomers to gain experience, often within internship programs. Medical Data Labeling Specialists are more experienced roles focused on precise data annotation for AI training, requiring relevant skills or certifications. While both involve working with medical data, internships are more educational, whereas specialists handle ongoing, professional data labeling tasks.

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Internship Medical Data Annotation jobs near you
Infographic showing various Internship Medical Data Annotation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Family Medicine / Primary Care Physician/MD (San Francisco based, Talent Network) Mercor · On s[...]

Dorado

San Francisco, CA • On-site

$210 - $250/hr

Other

Re-posted 4 days ago

Job description

Family Medicine / Primary Care Physician/MD (San Francisco based, Talent Network)

About the Role Mercor is taking applications for Family Medicine / Primary Care Physicians (PCPs)/MDs (general) on behalf of a healthcare AI partner building advanced clinical decision-support tools. We hire multiple experts on this role every few weeks. In this role you you will leverage your clinical expertise to review, annotate, and validate medical data, contributing directly to the development of safe, accurate, and explainable medical AI systems. This is an in person position based in San Francisco.

Key Responsibilities

Clinical Data Annotation: Review and label clinical text, EHR data, and case notes for use in AI model training. Identify and validate medical entities, diagnoses, treatment pathways, and outcomes relevant to family medicine.

Quality Review & Validation: Audit annotated datasets for clinical accuracy and consistency. Cross-check outputs generated by AI models to ensure medical soundness.

Knowledge Contribution: Provide expert input on guidelines for annotation, taxonomy development, and edge case definitions. Collaborate with data scientists and engineers to improve AI understanding of medical context.

Model Evaluation & Feedback: Evaluate AI-generated recommendations or clinical summaries, flag inaccuracies, and provide structured feedback for iterative model refinement.

Documentation & Training Support: Contribute to the creation of clinical documentation standards and assist in developing onboarding materials for new annotators.

Requirements

MD or DO degree with specialization in Family Medicine or Internal Medicine.

Board-certified or board-eligible in Family Medicine or Internal Medicine.

Academic hospital experience preferred

2+ years of clinical experience in in-patient or hospitalist care settings

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