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DataAnnotation seeks an experienced radiologist or imaging technologist to help train AI models by reviewing de-identified imaging studies and generating structured reports. You will document findings, impressions, and rationale to guide next iterations of imaging AI.
Responsibilities include dual-interpretation comparison, identifying where model reports miss or misstate information, and providing clear next steps for follow-up or workup, all in English and with rigorous documentation.
We’re looking for an experienced Radiologist to help train AI models. You’ll measure how well frontier models interpret medical images, check their reasoning, and help raise the quality of each new version.
This is a new and growing area: teaching AI to read diagnostic images, such as chest X-rays, ultrasounds, and nuclear medicine scans, the way a skilled radiologist would. The role is open to both radiologists and imaging technologists. Your reads, impressions, and written rationale become the signal that shapes the next generation of imaging AI.
Problems draw on whatever you know best:
Common backgrounds: Radiologist, Ultrasound Technologist, Nuclear Medicine Technologist.
Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.
DataAnnotation is where 100k+ experts train the world’s leading AI models. $150M+ paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.