Full-timeRemoteFixed budget for the 2-week project. Final amount depends on volume and team size.
AI Data Labeller – Object Detection (2-Week Project)
Overview
We're looking for experienced AI data labellers to help us build a high-quality object detection dataset over a 2-week sprint. This is hands-on labelling work where precision and consistency directly impact model performance.
You'll be annotating images for object detection, ensuring bounding boxes are accurate and metadata is clean. We're building infrastructure that scales, so we need people who understand what good labelling looks like and can maintain quality under timeline pressure.
This is a focused, remote project with a clear scope and fixed timeline. If you've labelled object detection datasets before and want to ship something real in two weeks, let's talk.
Required skills
AI data labellingobject detection datasetsattention to detailability to follow annotation guidelines
Nice to have
experience with labelling tools (CVAT, Labelbox, etc.)familiarity with COCO or Pascal VOC formatsprevious computer vision project experience
Deliverables
- ·Annotated image dataset with bounding boxes for object detection (quantity TBD based on scope)
- ·Labelled data in standard format (COCO JSON or equivalent)
- ·QA report documenting labelling consistency and any edge cases encountered
- ·Handoff documentation for downstream model training