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. 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 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 strong
reading comprehension — you'll 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). Robust 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.

📌 AI Video QC Annotator (New Delhi)
🏢 Welocalize
📍 New Delhi