Radiologic Technologist

We are seeking experienced, US-based Radiology Technicians to participate in a medical image segmentation annotation project. This project involves the precise segmentation of lesions identified in CT and MRI studies as part of a rigorous, multi-reader data labeling workflow designed to produce high-quality, adjudicated ground-truth masks for use in AI/ML model development. The project encompasses a total of 480 lesions — 240 CT and 240 MRI — each of which will be independently segmented by three (3) qualified radiology technicians. All completed segmentations will subsequently be reviewed, adjudicated, and if necessary corrected by a US Board-Certified (USBC) Radiologist.Annotation Workflow Step 1: Lesion Selection A US Board-Certified Radiologist will identify and select each lesion for segmentation across all CT and MRI cases. Technicians will work exclusively on pre-identified lesions; independent lesion discovery is not required. Step 2: Independent Segmentation (Technician Task) Each of the 480 lesions will be independently segmented by three (3) US-based Radiology Technicians. Technicians will: • Review the imaging study containing the designated lesion. • Perform a careful, slice-by-slice segmentation of the specified lesion boundary. • Complete work independently, without reference to other technicians' annotations. • Submit segmentation masks within the designated annotation platform and within agreed turnaround timelines.Step 3: Consensus & Radiologist Adjudication Following the collection of three independent segmentation masks per lesion, a US Board Certified Radiologist will: • Review the consensus mask derived from the three submissions. • Assess segmentation accuracy and agreement. • Make final adjustments to the segmentation where clinically necessary. The adjudicated mask will serve as the final ground-truth annotation for the lesion.Key Responsibilities • Accurately segment lesion boundaries in CT and MRI imaging datasets using the provided annotation platform. • Adhere strictly to the segmentation guidelines and quality standards established by the project radiologist team. • Complete assigned segmentations independently without collaboration with fellow annotators assigned to the same case. • Maintain a high level of anatomical accuracy and consistency in delineating lesion margins across imaging planes. • Meet project deadlines and turnaround time requirements for each batch of assigned lesions. • Flag ambiguous or technically challenging cases to the project supervisor promptly. • Participate in calibration exercises or training sessions as required to ensure annotation consistency.Required Qualifications • Active licensure or certification as a Radiology Technician in the United States (e.g., ARRT certification in Radiography, CT, or MRI). • Minimum of 2 years of hands-on clinical or research experience working with CT and/or MRI imaging. • Demonstrated proficiency in reading and interpreting cross-sectional imaging (CT and/or MRI). • Experience with or ability to quickly learn medical image annotation or segmentation software platforms. • Strong attention to detail, with the ability to work with precision and consistency across large imaging datasets. • Ability to work independently in a remote environment and meet project milestones. • Reliable high-speed internet connection and a suitable workstation for reviewing DICOM-quality imaging data.Preferred Qualifications • ARRT advanced certification in CT (CT) or MRI (MR). • Prior experience in medical imaging annotation, radiology AI data projects, or clinical research image analysis. • Familiarity with DICOM imaging format and annotation tools such as ITK-SNAP, 3D Slicer, MD.ai, Labelbox, or similar platforms. • Experience with oncologic or lesion-based imaging studies. • Background in cross-sectional body imaging, neuroradiology, or musculoskeletal imaging is a plus.