
Resident Medical Specialist (MD/DO)
Overview
This remote role places licensed physicians at the center of AI evaluation for clinical reasoning. You will design test scenarios, assessment frameworks, and gap analyses for medical AI systems, collaborating directly with AI researchers. The engagement is flexible and can fit around your clinical schedule, requiring up to 30 hours per week over a one-month contract, with possible extensions based on performance. Your hands-on medical judgment will shape how AI models handle real-world diagnostic and management problems.
What You'll Do6
- 1Collaborate with research teams to evaluate and improve how AI systems reason through clinical cases.
- 2Develop evaluation methods that test AI performance on real medical problems where clinical expertise matters.
- 3Create realistic clinical scenarios that challenge AI decision-making and diagnostic accuracy.
- 4Build assessment criteria that capture the subtleties of actual clinical practice.
- 5Identify weaknesses in AI medical knowledge and reasoning processes.
- 6Work with AI researchers to turn clinical insights into concrete model improvements.
Requirements4
- 1Hold an active medical license (MD or DO) and maintain current clinical practice in any specialty.
- 2Apply evidence-based medicine and clinical decision-making in everyday patient care.
- 3Show strong analytical skills and an ability to communicate clinical concepts clearly to engineers.
- 4Demonstrate genuine interest in how AI can support and enhance clinical practice.
Who Should Apply
This role suits a practicing physician who enjoys translating clinical experience into structured assessments for AI systems. Candidates without an active license or recent clinical practice will not fit, since the work demands current medical judgment. Applicants who struggle to explain clinical nuance to non-clinicians may find collaboration difficult. Common rejection reasons include lacking concrete examples of scenario design or showing no familiarity with AI evaluation methods. Specialists who prefer direct patient care over analytical, project-based work should probably pass on this engagement.
Location
Required Skills
Application Tip
When applying, describe a specific clinical case where your decision-making changed an outcome, and outline how you would turn that case into a test scenario for an AI model. Mention your specialty and years of active practice to signal immediate credibility.
See NearSkill jobs more often in your search
How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
Only candidates who clear screening move forward.
Similar open positions
Explore active roles that match your skills and interests.

Turing
VerifiedMedicine Physician (MD/DO/Doctoral study/PhD)
Turing, a San Francisco-based research accelerator, works with frontier AI labs and global enterprises to advance AI systems. This role puts licensed physicians at the center of evaluating how AI handles clinical reasoning. You will design evaluation methods for real medical problems, drawing on evidence-based medicine, and build assessment approaches that capture the nuance of clinical practice. The engagement is remote and flexible, up to 30 hours per week for one month, with possible extension based on performance.

Mercor
VerifiedClinical Medicine Domain Expert
A leading AI lab's GenAI team needs a practicing clinician to shape how frontier models reason about real clinical work. You will audit medical knowledge tasks for clinical soundness, write the instruction specs and golden solutions that set the standard for correctness, and design benchmarks that track model improvement. This full-time W-2 role runs through Cincinnatus LLC, with placement inside the client's own tools and workflows. Expect a hybrid schedule in the Bay Area, with on-site days each week, so local residency or a self-funded relocation is required.

SME Careers
VerifiedMedical Doctor Specialist for AI Content Review (Remote)
Work as a Medical Doctor Specialist SME, remotely on an hourly contract to review AI-generated clinical responses and, when needed, author expert medical content. You will assess clinical reasoning, verify step-by-step problem solving, and ensure responses align with the prompt. Your input helps improve AI models by validating accuracy, safety, and adherence to evidence-based guidelines. Specialists across fields including Internal Medicine, Emergency Medicine, and Cardiology are welcome to join the expert network.

Micro1
VerifiedMember of Technical Staff, Medical Research
Join a team focused on pushing the boundaries of AI in healthcare by designing evaluation frameworks and benchmarks for medical reasoning systems. As a Member of Technical Staff, you'll help shape how AI supports clinical decisions, evidence synthesis, and biomedical research. This remote role blends applied research with rigorous quality standards to build trustworthy healthcare AI.

Micro1
VerifiedMedical Evaluation Specialist - Remote Clinical QA for AI Training
Remote contractor role for medical professionals who will craft and verify high‑level medical QA pairs to train cutting‑edge AI. You’ll source answers from primary literature and guidelines, document rationale with citations, and design questions that require genuine clinical reasoning. You can expect to refine inputs based on reviewer feedback and evolving project standards. This work leverages your domain knowledge to improve model learning and evaluation, with tasks described and compensated per deliverable. Medical and clinical guidelines are central to every deliverable.

SME Careers
VerifiedMedical AI Content Expert for Remote Contract Work
This remote, hourly contractor role focuses on validating AI-generated medical responses and producing expert healthcare content. You’ll examine the reasoning steps, explain how evidence supports the conclusions, and deliver precise written feedback. You’ll flag unsafe assumptions, missing contraindications, or misinterpretations of tests to improve model reliability. Grounded in epidemiology and clinical medicine, your evaluations shape the accuracy and clarity of medical data used by leading AI initiatives.

