Remote | Medical Doctor - Physician Expert — $230/hour

24-Mag Llc; New York (NY); Hybrid; USD 261,000 - 372,000; Part time

Job summary

24-MAG LLC is inviting experienced Medical Doctors to contribute to AI training through remote clinical case review and medical annotation. You will assess AI-generated medical content, annotate patient cases, and provide expert feedback to improve AI-driven clinical reasoning.

The engagement is freelance/contract, part-time (approximately 15 hours per week minimum), fully remote within the United States, with compensation at $230 per hour. Up to 30 openings are available.

Qualifications

• MD with current or recent US clinical practice.
• Strong diagnostic analysis and physiology knowledge.
• Experience evaluating patient histories and clinical findings.
• Based in the United States.
• Good clinical judgement and data privacy adherence.

Responsibilities

• Review and annotate clinical scenarios and healthcare datasets.
• Assess accuracy and relevance of AI-generated medical information.
• Provide structured expert feedback on medical accuracy and reasoning.
• Collaborate with data scientists, engineers, and project stakeholders.
• Ensure patient data security and confidentiality.

Skills

Medical Doctor (MD)

Diagnostic analysis

Clinical medicine

Medical reasoning

Education

MD or equivalent

Medical residency

Tools

EHR review

Medical terminology

Job description

We are sharing a specialised remote consulting opportunity for experienced Medical Doctors with strong expertise in clinical medicine, diagnostic analysis, physiology, healthcare protocols, and medical decision-making to contribute their professional knowledge to advanced AI training and evaluation initiatives.

Selected professionals will review and annotate clinical scenarios, evaluate AI-generated medical information, and assess the accuracy and relevance of healthcare data. The work combines practical clinical expertise with structured medical reasoning, patient record analysis, and technical feedback to improve how advanced AI systems interpret clinical information and support medical decision‑making. Prior experience with AI training projects is not required.

Key Responsibilities

Clinical Case Review & Medical Annotation

• Review and annotate clinical scenarios, patient cases, and healthcare datasets.
• Analyse patient histories, clinical findings, and relevant medical documentation.
• Evaluate the accuracy, completeness, and clinical relevance of annotated healthcare information.
• Identify inconsistencies, unsupported conclusions, and missing clinical details.
• Apply professional medical knowledge to support the development of high-quality AI training datasets.

Diagnostic Analysis & Medical Reasoning

• Apply diagnostic reasoning to evaluate complex clinical presentations and patient information.
• Assess the consistency of medical conclusions with documented clinical findings.
• Incorporate knowledge of general medicine, physiology, and healthcare protocols into clinical evaluations.
• Identify inaccurate interpretations, incomplete assessments, and weaknesses in medical reasoning.
• Provide clinically grounded explanations to support improvements in AI-generated medical content.

AI Medical Content Evaluation & Quality Assurance

• Review AI-generated medical information for clinical accuracy, relevance, and consistency.
• Evaluate medical outputs against appropriate clinical standards and established healthcare practices.
• Identify opportunities to improve the reliability of AI-generated clinical explanations and recommendations.
• Provide structured expert feedback on medical accuracy, reasoning quality, and information completeness.
• Support the refinement of evaluation criteria and healthcare data quality standards.

Healthcare Documentation & Clinical Workflow Analysis

• Review electronic health records, patient data, and clinical documentation relevant to assigned tasks.
• Interpret medical terminology and translate complex clinical concepts into clear evaluation guidance.
• Assess healthcare workflows and documentation practices using practical clinical experience.
• Identify discrepancies between medical records, clinical interpretations, and expected healthcare procedures.
• Maintain appropriate standards of patient data security, privacy, and professional confidentiality.

Technical Feedback & Cross-Functional Collaboration

• Prepare clear written evaluations documenting clinical findings and recommended improvements.
• Collaborate with data scientists, engineers, and project stakeholders on medical evaluation requirements.
• Explain clinical concepts, diagnostic considerations, and medical terminology to multidisciplinary teams.
• Contribute professional insights to improve AI training workflows and project deliverables.
• Maintain consistent accuracy, attention to detail, and ethical standards across assigned work.

Ideal Profile

• Medical Doctor (MD or equivalent medical qualification) with current or recent U.S. clinical practice experience.
• Completion of medical residency is preferred; physicians in their final year of residency may also be considered.
• Strong professional expertise in diagnostic analysis and general clinical medicine.
• Advanced understanding of human physiology and its application to clinical decision‑making.
• Familiarity with established healthcare protocols and clinical standards of care.
• Experience evaluating patient histories, clinical presentations, and medical findings.
• Strong clinical reasoning skills and the ability to assess complex diagnostic scenarios.
• Clinical experience in Internal Medicine, Family Medicine, or Emergency Medicine is particularly relevant.
• Physicians from selected medical subspecialties may also be considered.
• Demonstrated ability to interpret medical terminology accurately.
• Experience reviewing electronic health records and patient documentation.
• Familiarity with clinical data analysis and medical record evaluation.
• Ability to identify inaccuracies, inconsistencies, and incomplete information in medical content.
• Strong analytical reasoning and attention to detail.
• Excellent written communication skills for explaining medical assessments and technical findings.
• Effective verbal communication and ability to collaborate with multidisciplinary teams.
• Ability to translate complex clinical concepts into clear, actionable recommendations.
• Understanding of healthcare documentation standards and clinical workflows.
• Strong professional judgement when evaluating AI-generated medical information.
• Commitment to patient data confidentiality, information security, and ethical handling of healthcare information.
• Ability to work independently and maintain consistent quality across assigned evaluations.
• Strong organisational skills and reliability in meeting project requirements.
• Previous experience with clinical quality assurance, medical annotation, or structured chart review is advantageous.
• Must be based in the United States.
• Prior experience with AI model training or evaluation projects is not required.

Engagement Details

• Freelance / contract engagement
• Part-time — approximately 15 hours per week minimum
• Fully remote — United States only
• Compensation: $230/hour
• 30 available openings
• Professional Focus: Clinical medicine, diagnostic analysis, medical reasoning, and healthcare data evaluation.
• Preferred Background: Current or recent U.S. clinical practice, with completed residency or final‑year residency status.
• Relevant Specialties: Internal Medicine, Family Medicine, Emergency Medicine, and selected subspecialties.
• Technical Focus: Patient case annotation, EHR review, medical terminology, physiology, and clinical documentation.
• Evaluation Focus: Medical accuracy, diagnostic reasoning, healthcare protocols, and AI-generated clinical content.
• Responsibilities will include reviewing patient scenarios, annotating medical data, and evaluating AI-generated healthcare information.
• Assignments may involve assessing diagnostic conclusions, interpreting clinical documentation, and identifying improvements to medical data quality.
• Deliverables will include structured medical annotations, clinical evaluations, and detailed written feedback.
• Selection Process: An initial AI-assisted conversational interview of approximately 25 minutes, followed by a short questionnaire and project‑team review for progressing candidates.
• Onboarding Timeline: Selected professionals are generally expected to begin their first assignments within 24–48 hours of receiving project credentials.
• Strong clinical judgement, clear communication, and consistent adherence to data privacy requirements are important for successful participation.
• Previous experience with AI training projects is not required.

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project‑based workstreams.

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