Radiologist - Chest/Thoracic Structural Annotation Specialist (Remote, Short-Term)
Job Description
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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 a 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 an active license.
Experience: 3–10 years of 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.
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Aptura
View Company ProfileAptura AI is a premier, enterprise-grade data marketplace and AI training infrastructure platform engineered to orchestrate massive-scale proprietary dataset curation and intelligent, domain-expert RL environment workflows. Operating as a trailblazer in high-integrity data licensing and agent evaluation for regulated industries, the company eliminates the operational friction of traditional AI data acquisition—which frequently suffers from unverified scraping sources, severe compliance risks, and low-fidelity domain reasoning—by seamlessly deploying specialized expert annotation networks, verifiable task benchmarks, and zero-trust data licensing frameworks. Moving beyond generic web-scraped training corpora, Aptura AI empowers leading AI research labs, frontier model developers, and enterprise AI teams to dynamically source, license, and evaluate complex domain datasets across financial modeling, clinical oncology, and M&A legal frameworks with elite, scalable, and audit-ready precision. Under the hood, its sophisticated proprietary operational infrastructure—bolstered by strict data privacy safeguards, verifiable task-evaluation environments, and closed-loop domain expert feedback systems—natively manages high-stakes data ingestion, reinforcement learning from human feedback (RLHF), and compliant cross-border data transfer workflows, providing the necessary foundation for reliable frontier model deployment. What sets Aptura AI apart is its uncompromising dedication to high-precision domain alignment; by bridging the gap between deep specialized human expertise and next-generation AI model architectures, the firm enables frontier AI organizations to radically accelerate model accuracy, eliminate hallucination vectors in critical sectors, and build an unassailable foundation for trustworthy artificial intelligence in modern enterprise ecosystems.
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