Breast Imaging Radiologist

**Pay:** $300 per hour (USD). Mercor is hiring fellowship-trained breast imaging radiologists (MDs and DOs) to help build rigorous evaluations of how well AI reads real imaging studies, in partnership with a leading AI lab. This is not image labeling. You will read de-identified studies, write the reference finding or report, and review AI-drafted reads to mark what is inaccurate, unsupported, or unsafe. Your clinical judgment becomes the reference standard that trains and tests frontier models, work that improves outcomes for millions of patients around the world. **Key Responsibilities** - Read de-identified screening and diagnostic mammography, tomosynthesis, breast ultrasound and breast MRI studies and record the reference finding - Apply the structured systems and measurement conventions you use in practice (BI-RADS and related standards) - Review AI-generated reads and flag errors that are inaccurate, unsupported, or could compromise patient safety - Write structured rationales on clinical rigor, completeness and clarity **Required Qualifications** - **MD or DO** from a medical school in the United States - Board certified in **ABR Diagnostic Radiology** through an ABMS member board or the AOA - Completed a breast imaging or women's imaging fellowship - Active, unrestricted US medical license - **Currently practicing** and reading breast imaging in the US, with at least 5 years of independent practice after training - Resident in the US, outside California - Clear written communication and close attention to detail **Project Details** - Remote and hourly, with flexible part-time hours - Start date: immediate **Application & Onboarding** - Upload your resume - Complete a 25-minute conversational interview on your background, experience and motivations - Credential verification: license status, board certification, training and current practice setting - Receive next steps and onboarding details within a few days Apply today and put your clinical expertise to work shaping the imaging models clinicians and patients will rely on.