Project Cursa - Robot Manipulation Video Annotation QC (V2)
Welo Data · Philippines · Data annotation / labeling
Project Cursa - Robot Manipulation Video Annotation QC (V2) is an open role at Welo Data, located in Philippines.
Applications open on Welo Data’s own site. How we make money.
At a glance
- Pay
- Not disclosedWelo Data doesn't publish a rate for this listing
- Location
- Philippines
- Work type
- Data annotation / labeling
- Listed
- Since Aug 22, last confirmed Oct 24
From Welo Data’s listing
“About the Role We are looking for a detail-oriented QC Reviewer to ensure the quality and consistency of robot manipulation video annotations produced by our annotation team.”
Show the full listing
About the Role We are looking for a detail-oriented QC Reviewer to ensure the quality and consistency of robot manipulation video annotations produced by our annotation team. You'll review labeled video segments against a detailed style guide and reference examples, catch errors or inconsistencies, and provide clear, constructive feedback to annotators. This role is critical to maintaining the accuracy and reliability of training data used for robotics AI models. What You'll Do - Review completed annotations of robot manipulation videos across three levels of labeling detail (atomic motion, skill/subtask, task/goal). - Cross-check annotator descriptions against all three camera views (overhead and both wrist-mounted cameras) to verify accuracy of described actions, object identification, and contact/grasp details. - Verify full coverage of each video — confirm there are no gaps in labeling, including idle or pause moments. - Check that descriptions accurately reflect what actually happened in the video, including failures, drops, or slipped grips — flagging any instances where outcomes were inaccurately described or "smoothed over." - Evaluate annotations for adherence to the style guide: correct vocabulary usage, spatial/directional accuracy, consistent terminology for objects and actions, and appropriate language variation (avoiding repetitive phrasing). - Identify recurring errors or patterns of confusion among annotators and report them to the team lead for calibration purposes. - Provide specific, actionable feedback on rejected or revised annotations, referencing the style guide and reference examples. - Participate in periodic calibration sessions with the team and client to align QC standards with evolving guidelines or edge-case resolutions. - Maintain a QC log or tracking sheet documenting review outcomes, common error types, and annotator performance trends (as required by the project). What We're Looking For Required: - Excellent written English and stro
About Welo Data: part of Welocalize. See the full profile →
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Frequently asked questions
How do I apply for the Project Cursa - Robot Manipulation Video Annotation QC (V2) role at Welo Data?
Applications go through Welo Data's own portal - HumanSourcer links to the listing and never collects applications or handles hiring. Welo Data's access model is "Open / self-serve" (Join community). This listing was first seen here on August 22, 2026 and was still live at the last check.
Is the Project Cursa - Robot Manipulation Video Annotation QC (V2) role at Welo Data remote?
This role is listed for: Philippines.
What does the Project Cursa - Robot Manipulation Video Annotation QC (V2) role at Welo Data pay?
Welo Data doesn't state a rate on this listing. HumanSourcer never fills that gap with an estimate, so the absence is the source's, not a hole in this page. Welo Data's profile shows what its rate-carrying listings do advertise.
What kind of work is Project Cursa - Robot Manipulation Video Annotation QC (V2)?
Data annotation / labeling. Multilingual evaluation, AI safety, search relevance and annotation
Is Welo Data a legitimate AI-training platform?
Welocalize AI-data community - and that relationship is rated "Confirmed" here because it can be checked against welodata.ai rather than taken on Welo Data's word. Confidence describes how well the ownership is evidenced. It is not a rating of how the platform treats the people who work for it, which no public source covers reliably.
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