SAIGroup
Contract Radiology Technologist – CT/MRI Image Segmentation
Skills
2 months ago
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Important information
Contract type:
Part time
Location:
Bengaluru, Karnataka, India
Work mode:
Remote
Published on:
1 September 2026
What they need
Location: Bengaluru preferred | Remote candidates considered
Engagement: Contract / Per-image payment
Organization: TeraRecon
About the Role TeraRecon Insight is looking for Radiology Technologists to support the development and training of our next-generation AI foundation models for medical imaging.
The role involves segmenting and annotating anatomical structures and relevant findings on raw CT/MRI images using our image annotation/segmentation tools. The work will directly contribute to building high-quality datasets for AI model training and validation.
Key Responsibilities
- Perform accurate segmentation of anatomical structures and imaging regions on CT/MRI studies.
- Follow predefined clinical annotation and segmentation guidelines.
- Review images for segmentation quality and completeness.
- Maintain consistency and accuracy across large volumes of imaging studies.
- Collaborate with the AI/clinical team to improve annotation guidelines and workflows.
Requirements
- Degree/Diploma in Radiology Technology / Medical Imaging Technology or equivalent.
- Hands-on experience working with CT and/or MRI images.
- Good understanding of cross-sectional anatomy and radiology imaging.
- Strong attention to detail and ability to perform repetitive, high-accuracy annotation work.
- Prior experience with medical image segmentation, annotation, PACS, 3D visualization, or AI datasets is a strong plus.
Engagement Model
- Contractual / project-based engagement.
- Payment will be based on completed and quality-approved image segmentations.
- Technologists are expected to have their own laptop/computer and reliable internet connection.
- Bengaluru-based candidates are preferred, but remote candidates across India are welcome.
Interested? Please share your CV/profile, location, years of CT/MRI experience, and any prior experience with medical image annotation/segmentation .
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