AI Work Central

Radiologist

SME CareersMedicineFirst seen 9 Oct 2026

up to$120/hr as listed by SME Careers, USDEstimate a week at this rate
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Where
17 countries

United States, Germany, Brazil, India, Bangladesh, Bhutan, Indonesia, Cambodia, Sri Lanka, Malaysia, Nepal, Philippines, Pakistan, Singapore, Thailand, Timor Leste, Vietnam

Language
English
Type
Contract, remote

Posted on SME Careers First seen 9 Oct 2026Checked 12 Oct 2026

From the SME Careers listing

In this hourly, remote contractor role, you will work as a Radiologist Subject Matter Expert (SME) to review AI-generated radiology and medical-imaging responses and/or create expert imaging content, evaluating reasoning quality and step-by-step clinical problem-solving while providing precise written feedback. You will assess solutions for accuracy, clarity, safety, and adherence to the prompt; identify errors in imaging appropriateness, differential diagnosis reasoning, modality selection, protocol choices, incidental findings logic, and patient-safety considerations (contrast, radiation, pregnancy, allergies, renal function); fact-check imaging and clinical information; write high-quality explanations and model solutions that demonstrate correct reasoning; and rate and compare multiple responses based on correctness and reasoning quality.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your radiology expertise directly helps improve the world’s premier AI models by making their imaging decision-making, interpretation reasoning, and patient-facing explanations more accurate, reliable, and clearly explained.

Important:

There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

  • Develop AI Training Content: Create detailed prompts and gold-standard answers across imaging appropriateness, protocols, differential diagnosis, and radiology reporting concepts.
  • Optimize AI Performance: Evaluate and rank AI responses to improve clinical correctness, safety, clarity, and contextual fit.
  • Ensure Model Integrity: Test AI outputs for inaccuracies, unsafe imaging recommendations, and bias; validate reliability across patient populations and use cases.

Requirements

  • MD/DO (or equivalent) with completed Radiology residency (Diagnostic Radiology) and board eligibility/certification (or local equivalent).
  • 5+ years of professional experience in radiology practice (academic, community, teleradiology, or subspecialty practice).
  • Strong clinical reasoning: translating clinical presentations into imaging strategy; constructing and prioritizing differentials based on imaging + context.
  • Deep understanding of imaging modalities and tradeoffs (sensitivity/specificity, limitations, artifacts, protocol impacts).
  • Excellent safety judgment: contrast reactions, nephrotoxicity risk, pregnancy considerations, anticoagulation/procedure risks, radiation dose principles.
  • Exceptional attention to detail when fact-checking and identifying unsafe assumptions, missed “can’t-miss” diagnoses, or misleading explanations; minimum C1 English proficiency.
  • Comfortable evaluating answers for internal consistency (clinical story → modality → findings → impression → next steps), appropriateness by setting (ED vs outpatient vs inpatient), and patient-safety implications.
  • Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
  • Prior experience with AI data training/annotation, report QA, peer review, utilization management, or medical editorial work is strongly preferred.

Text above is the platform's own listing, shown as published. Check the details on SME Careers before applying.

Prepare for the assessment

Practice questions and what each platform says about its screening for this kind of role:

Terms in this listing

  • Prompt: The input given to a model: a question, an instruction or a conversation so far.
  • Fact-checking: Checking each claim in a model's answer against reliable sources and marking what is wrong or unsupported.
  • Annotation: Adding labels or notes to data such as text, images, audio or video so a model can learn from it.

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