AI Video QC Annotator
关于角色 我们正在寻找一个详细的 QC 评审员，以确保我们注释团队所制作的机器人操纵视频说明的质量和一致性。你将根据详细的风格指南和参考示例进行标签的视频段口述，捕获错误或不一致性，并向注释人员提供明确，建设性的反。这个职位对于保持用于机器人人工智能模型的培训数据的准确性和可靠性至关重要。项目详情：· 工作称号：Cursa - Robot Manipulation Video Annotation QC · 地点：印度/菲律宾 /埃及/墨西哥 · 远程工作类型：自由职业 · 付费率：4.03美元 / 小时 你会做什么？· 审查完成的标签视频说明 （原子运动，技能/子任务，任务/目标）. · 对三个摄像头观看 （上头和两只手腕安装摄像机）的注释器描述进行交叉检查，以验证所述行动的准确性，对象识别和接触/抓取细节。· 确认每个视频的完整覆盖度。确认没有标记中空隙，包括置或停顿时刻。· 检查描述是否精确反映了实际发生在视频中的事件，包括故障，落下或滑动抓住。· 评估注释以遵守风格指南：正确的词汇使用，空间/方向准确性，对物体和行动的一致术语以及适当的语言变化 （避免重复表达）. · 识别注释者之间的反复错误或混乱模式并将其报告给团队领导进行校准。· 提供针对拒绝或修改的注释的具体可操作反，引用风格指导书和参考示例。· 与团队和客户一起参加定期校准会议，以便与不断发展的指南或边缘案例解决方案协调 QC 标准。· 保持一个 QC 日志或跟踪表，记录审查结果，常见的错误类型和注释器性能趋势 （根据项目要求）.我们正在寻找什么：· 精致的写作英语和强大的阅读理解。· 你将评估准确的，微妙的语言选择，而不仅仅是检查字体错误。· 特别关注细节。
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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/Egypt/Mexico
- 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).
· 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.
Originally posted on Himalayas