Manual Structural Crack Segmentation Annotator
About the role
OpenTrain AI is hiring an annotator to manually segment structural cracks in high-resolution UAV bridge imagery for a short-term research project. Work is entirely manual — no AI-assisted tools — and supports a ground-truth and inter-annotator agreement study; a smaller pilot is completed first before the remaining dataset is assigned.
What you'll do
- Create pixel-level polygon or brush annotations of visible structural cracks in UAV bridge imagery using Roboflow.
- Zoom and inspect high-resolution images (some 8192×5460px) to distinguish cracks from joints, shadows, stains, and vegetation.
- Exclude construction/expansion joints, formwork lines, and non-structural background elements.
- Mark uncertain features or add review comments rather than forcing a classification.
- Complete a pilot assignment first; continued work depends on meeting quality and consistency standards.
Requirements
- Intermediate-level manual polygon or segmentation annotation experience.
- At least 20 hours of weekly availability.
- Preferred civil, infrastructure, bridge, structural, or defect-inspection experience.
- Strong accuracy and attention to detail on detailed imagery.
- Basic English proficiency.
- Manual annotation only — no AI-assisted tools (SAM, Smart Polygon, Auto Label, etc.) permitted.
About OpenTrain AI
OpenTrain AI is a talent marketplace connecting freelance AI trainers and domain experts with AI training and data-labeling projects; candidates apply through OpenTrain, which may place or refer them to the client whose project they support.
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