AI Video QC Annotator

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. Youll 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.

Project Details:

• Job Title: Project Cursa - Robot Manipulation Video Annotation QC
• Location: Remote in India/Philippines
• Employment type: Freelance
• Pay Rate: US$4.03/hour

What Youll 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 Were Looking For

Required:

• Excellent written English and strong reading comprehension youll be evaluating precise nuanced language choices not just checking for typos.

• Exceptional attention to detail able to catch subtle mismatches between video content and written description (e.g. a mislabeled grasp type an incorrect object part a missed failure event).

• Strong grasp of spatial/mechanical description (left/right above/below object parts like handles lids edges) to verify annotator accuracy.

• Ability to apply a detailed structured style guide consistently and make sound judgment calls in ambiguous or edge-case scenarios.

• Comfort giving clear specific and constructive feedback to annotators (written feedback not just pass/fail marks).

• Reliable self-directed work habits with the ability to work independently while meeting review turnaround expectations.

Nice to Have:

• Prior experience in a QC editing proofreading or annotation review role.

• Experience with video annotation data labeling or transcription QA specifically.

• Familiarity with robotics terminology (grippers end-effectors manipulation).

• Experience with annotation tools such as Label Studio including review/approval workflows.