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DataAnnotation seeks experienced radiologists or imaging technologists to train AI models by reviewing chest X-rays, ultrasounds, and nuclear medicine studies. You will write structured reports, document findings, impressions, and follow-up steps, and compare independent interpretations to improve model accuracy.
The role emphasizes clear rationale, detail orientation, and the ability to explain why a report may be incorrect or incomplete.
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.