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Home Based Medical Data Annotation Jobs (NOW HIRING)

Sunday

Technical Program Manager, Data Engine

Redwood City, CA · On-site

$157K - $204K/yr

... data annotation or collection • Ability to leverage AI to help improve productivity Company : Sunday is a robotics and artificial intelligence company that develops an autonomous home robot to ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

Here's a job summary in list format based on your description for the Data Annotator & QA Reviewer (Autonomy & Robotics - Mining Operations): --- ### Job Summary - Perform Manual Data Annotation & QA ...

TSMG Holding

AI/ML Data Contributor

Indianapolis, IN · On-site

... based testing. Responsibilities : • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation • Participate in remote assignments or attend on-site sessions when ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

... based vendors and external partners. • Strong problem-solving skills and ability to operate ... with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

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Home Based Medical Data Annotation information

What are some common challenges faced by professionals working in home based medical data annotation, and how can they be managed?

One common challenge in home-based medical data annotation is maintaining accuracy and consistency when labeling complex medical images or records, as errors can impact critical healthcare outcomes. Working remotely may also lead to feelings of isolation or difficulty staying updated with annotation guidelines. To manage these challenges, it's important to establish a quiet, dedicated workspace, participate in regular virtual team meetings, and utilize provided training resources. Staying engaged with peers through communication channels and seeking feedback from supervisors can also help ensure high-quality work and ongoing professional development.

What are the key skills and qualifications needed to thrive as a home based medical data annotation specialist?

To thrive as a Home Based Medical Data Annotation Specialist, you need a solid understanding of medical terminology, attention to detail, and experience with data labeling—often supported by a background in healthcare or life sciences. Familiarity with annotation platforms, EHR systems, and relevant data security protocols is typically required, and some employers may prefer certifications in medical coding or data management. Strong organizational skills, self-motivation, and effective written communication help individuals excel in remote, deadline-driven environments. These competencies ensure accurate, high-quality data labeling that is essential for developing reliable AI systems in healthcare.

What is the difference between Home Based Medical Data Annotation vs Home Based Medical Transcription?

AspectHome Based Medical Data AnnotationHome Based Medical Transcription
Required CredentialsBasic medical knowledge, attention to detailMedical terminology, transcription skills, sometimes certification
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, data labeling for healthcare AI modelsConverting audio to written reports for medical records
Common Search/ComparisonYesYes

Home Based Medical Data Annotation involves labeling medical images and data to train AI systems, requiring attention to detail and basic medical knowledge. In contrast, Home Based Medical Transcription focuses on converting audio recordings into written medical reports, often needing transcription skills and familiarity with medical terminology. Both roles are remote and industry-specific, but they serve different purposes within healthcare technology and documentation.

What is home based medical data annotation?

Home based medical data annotation involves labeling and categorizing medical data, such as images, audio, or text, from the comfort of your home. Annotators help train artificial intelligence (AI) systems by identifying and marking relevant information, such as highlighting tumors in X-rays or transcribing medical notes. This role is essential for improving the accuracy and efficiency of AI tools used in healthcare diagnostics, research, and patient care. Typically, it requires attention to detail, a basic understanding of medical terminology, and familiarity with annotation tools.
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Home Based Medical Data Annotation jobs near you
Infographic showing various Home Based Medical Data Annotation job openings in the United States as of August 2026, with employment types broken down into 64% Full Time, 22% Part Time, and 14% Contract. Highlights an 81% In-person, and 19% Remote job distribution.

Family Medicine / Primary Care Physician (San Francisco based) (Train AI Models Part Time!)

慨正橡扯

San Francisco, CA • On-site

$200 - $300/hr

Other

Re-posted 4 days ago

Job description

About the Role

Mercor is hiring Family Medicine / Primary Care Physicians (PCPs) on behalf of a healthcare AI partner building advanced clinical decision‑support tools. In this role, 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.
  • Active medical license in good standing.
  • Academic hospital experience preferred.
  • 2+ years of clinical experience in in-patient or hospitalist care settings.
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