Radiologist - Chest CT Annotation - AI Project (USA)

We are seeking radiologists with a chest/thoracic background to carry out structural annotation on de-identified chest CT scans, with a focus on spatial accuracy and consistency against detailed annotation guidelines.

You will work asynchronously on a dedicated annotation platform, marking points, boxes and measurements on findings that have already been flagged upstream, to support the development of clinical AI imaging models.

This is a remote, flexible and short-term project.

Key Responsibilities:

• Click-point placement: Mark specific coordinates on a scan, such as the centre of a nodule.
• Bounding boxes: Draw boxes around defined regions of interest, such as a flagged lesion.
• Simple measurements: Record diameter, or distance between two marked points, on segmentations or polygons already drawn.
• Guideline application: Work to an annotation guideline covering placement conventions, boundary definitions and measurement rules, applied consistently across a large volume of studies.
• Edge case handling: Flag ambiguous cases with a short rationale so guidance can be refined.
• This is structural markup project with no interpretation required. You will not be reading scans for diagnosis, judging malignancy, or making clinical decisions.

Qualifications:

• Registration: Registered radiologist in your country of practice with active license
• Experience: 3–10 years' experience in radiology, with a chest/thoracic focus
• Knowledge: Strong grounding in thoracic anatomy and cross-sectional CT.
• Attention to detail: Proven accuracy and consistency in image review or measurement work.
• Technical proficiency: Comfortable using structured annotation tools and digital platforms.
• Prior imaging annotation experience is an advantage but not required.
• Language: Native or near-native written English.
• Legal Status: You will have the right to work in your country of residence.
• You will work as an independent contractor.
• Why Join Us?
• Flexible Work Arrangements: Part-time, remote and fully asynchronous.
• Competitive Compensation: Hourly rate, paid weekly.
• Professional Development: Hands-on experience in clinical AI development and medical imaging, shaping how AI systems localise and measure findings on CT.