Project Cursa - Robot Manipulation Video Annotation QC

Welocalize, Inc.; Philippines; Remote; PHP 420,000 - 660,000; Full time

Job summary

Welocalize, Inc. is seeking a detail-oriented QC Reviewer to ensure the quality and consistency of robot manipulation video annotations produced by our annotation team.

You will review labeled segments against a detailed style guide and reference examples, catching errors and providing constructive feedback to annotators. This remote, project-based role requires excellent English, strong attention to detail, and the ability to evaluate captions and object labels across multiple camera views.

Qualifications

• Detail-oriented QC Reviewer for robot manipulation video annotations.
• Able to spot subtle mismatches between video content and descriptions.
• Excellent command of English and precise language usage.
• Capable of giving clear, actionable feedback to annotators.

Responsibilities

• Review robot manipulation video annotations across three labeling levels.
• Cross-check descriptions against multiple camera views for accuracy.
• Ensure full coverage with no gaps or idle moments in labeling.
• Flag incorrect or smoothed descriptions and document issues per style guide.

Skills

Attention to detail

Excellent written English

Strong reading comprehension

Constructive feedback

Independent work

Tools

Label Studio

Job description

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.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.