Diagnostic Radiologist - AI Trainer

DataAnnotation; Palo Alto (CA); Remote; USD 142,000 - 202,000; Full time

Benefits offered by this job

Flexible, remote work

Project-based engagement

Job summary

DataAnnotation is seeking an experienced Radiologist or imaging technologist to help train AI models by reviewing studies and generating structured reports. You will compare interpretations, log discrepancies, and pinpoint gaps in model-generated reports to improve subsequent AI versions.

Responsibilities include reviewing de-identified chest X-rays, ultrasounds, and nuclear medicine scans with clinical context, writing impressions and recommendations, and documenting rationale to support model

Qualifications

• A residency-trained or board-certified radiologist, or a credentialed or licensed imaging technologist.
• Hands-on experience performing or interpreting studies.
• Clear, well-organized writing, and the ability to say why a report is wrong, not only that it is.
• Detail-oriented.

Responsibilities

• Review de-identified studies (chest X-rays, ultrasounds, nuclear medicine scans) alongside their clinical context.
• Write comprehensive, structured reports documenting every finding, including subtle and incidental ones.
• Give clear impressions and recommend next steps, such as follow-up scans or further workup.
• Compare two independent interpretations of the same study, resolve the differences, and log each discrepancy.
• Pinpoint what model-generated reports miss, misstate, or leave incomplete.

Skills

English fluency

Radiology board certification

Interpret imaging studies

Clear writing

Detail-oriented

Education

Residency-trained radiologist

Board-certified radiologist

Credentialed imaging technologist

Licensed imaging professional

Job description

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.

What you’ll actually do

• Review de-identified studies (chest X-rays, ultrasounds, nuclear medicine scans) alongside their clinical context.
• Write comprehensive, structured reports that document every finding, including subtle and incidental ones.
• Give clear impressions and recommend next steps, such as follow-up scans or further workup.
• Compare two independent interpretations of the same study, resolve the differences, and log each discrepancy.
• Pinpoint what model-generated reports miss, misstate, or leave incomplete.

Problems draw on whatever you know best:

• Radiography: chest and musculoskeletal plain film.
• Ultrasound and sonography.
• Nuclear medicine and molecular imaging.
• Cross-sectional imaging: CT and MRI.
• Subspecialty reads: neuro, body, cardiothoracic, and emergency.

Roles this fits

Common backgrounds: Radiologist, Ultrasound Technologist, Nuclear Medicine Technologist.

What we look for

• Fluency in English (native or bilingual level).
• A residency-trained or board-certified radiologist, or a credentialed or licensed imaging technologist (radiologic, ultrasound, or nuclear medicine).
• Hands-on experience performing or interpreting studies.
• Clear, well-organized writing, and the ability to say why a report is wrong, not only that it is.
• Detail-oriented.
• Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States will be considered for this role.

Compensation

Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.

About DataAnnotation

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.