Project Cursa - Robot Manipulation Video Annotation QC
关于角色 我们正在寻找一个细节导向的 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。你将对标签视频段进行详细风格指南和参考示例的审查，捕获错误或不一致性，并为注释人员提供明确，建设性的反。这项职能对于保持用于机器人人工智能模型的训练数据的准确性和可靠性至关重要。· 检查描述符的描述与所有三个摄像头视图 （上部和两支手腕安装摄像机）来验证所述操作，对象识别和接触/抓取细节的准确性。· 检测每个视频的完整覆盖情况。·确认没有标签中空白，包括置或暂停时刻。· 确保说明书精确反映了视频中的实际事件，包括失败，落下或滑动的抓住。确定注释者之间的反复出现的错误或混模式，并将其报告给团队负责人进行校准。·提供针对拒绝或修改的注释的具体可操作反，引用风格指南和参考示例。·与团队和客户一起参加定期校准会议，以使 QC 标准与不断变化的指导方针或边缘案例解决方案保持一致。· 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）.我们需要什么：· 优秀的写作英语和强大的阅读理解。· 你将评估精确的，微妙的语言选择，而不仅仅是检查字体错误。· 特别关注细节。· 能够应用详细的信息
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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.
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.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Originally posted on Himalayas