Data Annotation Contributor
About the role
HumanSignal is building a global community of detail-oriented contributors to improve AI training datasets. As a Data Annotation Contributor, you'll review and correct labeled data in images and videos — bounding boxes, segmentation masks, and PII masking — for AI and computer vision systems. Projects are flexible and project-based; contributors choose which initiatives to join. Philippines is explicitly listed as an eligible country.
What you'll do
- Review and correct bounding boxes around objects or people in images and video
- Adjust or refine segmentation and masking areas within images
- Identify and mask personally identifiable information (PII) when required
- Ensure annotations follow detailed project guidelines and quality standards
- Flag unclear or incorrect labels for review and submit completed tasks via designated tools
Requirements
- Must reside in an eligible country — Philippines is confirmed on the list
- Detail-oriented with ability to follow structured quality guidelines consistently
- Comfortable working independently and managing tasks responsibly
- Strong communicator for raising questions or flagging edge cases
- Comfortable using online tools for reviewing and editing labeled data
- Prior annotation or image labeling experience is a plus but not required
About HumanSignal
HumanSignal is a human data partner for companies building AI models and products, combining real-world data creation, annotation, and delivery services with Label Studio — the open-source industry-standard platform for data labeling used by over 1 million practitioners worldwide.
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