OverviewJob Type: Part-time, contract (min. ~15 hs a week)
Location: Remote
About Us:
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Job SummaryJoin our customer's team as a Radiologist and make a direct impact on the future of medical imaging. In this role, you will leverage your clinical expertise to review, annotate, and provide feedback on radiological data, directly influencing the accuracy and reliability of cutting-edge AI models. Collaborate remotely with a passionate team advancing healthcare technology.
Responsibilities
Review and annotate radiological images, including CT, MRI, and X-ray scans, for the training and validation of AI algorithms.
Assess AI-generated reports for diagnostic accuracy, clinical clarity, and alignment with established medical standards.
Deliver expert feedback on model performance, edge cases, and diverse clinical scenarios to facilitate ongoing improvement.
Work closely with AI researchers and data teams, ensuring model outputs are clinically relevant and robust.
Maintain strict adherence to clinical guidelines, ethical standards, and data privacy protocols when interpreting medical data.
Identify potential improvements in annotation processes and share insights to refine AI learning strategies.
Communicate findings and feedback clearly through both written documentation and verbal discussions with cross-functional teams.
Required Skills and Qualifications
A minimum of 3–5+ years of clinical imaging experience.
Being a Board-certified Radiologist
Demonstrated expertise in diagnostic accuracy across major modalities (CT, MRI, X-ray).
Strong clinical communication skills, both written and verbal, with a keen attention to detail.
Experience with PACS and radiological reporting tools for image assessment and workflow integration.
Ability to critically evaluate image quality and detect subtle pathologies.
Proficiency in English is required, especially for providing clear, constructive written feedback.
Commitment to a minimum of ~15 hours per week for AI training participation. Fewer weekly hours of availability are also welcomed.
Preferred Qualifications
Interest in technology-driven healthcare innovation and model development best practices.
Experience collaborating with technical teams in an interdisciplinary environment.
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