Project Cursa - Robot Manipulation Video Annotator (V2)

About the Role We are looking for detail-oriented annotators to help label robot manipulation videos for AI training purposes. You'll watch short videos of robots performing manipulation tasks (filmed from three synchronized camera angles) and produce precise, structured, natural-language descriptions of the actions taking place. This work directly supports the development of robotics AI models and requires strong written English, sharp observational skills, and the discipline to follow a detailed style guide consistently. What You'll Do 1. Watch short robot manipulation videos, each filmed from three synchronized camera views (an overhead view and views from each of the robot's two wrist-mounted cameras). 2. Break each video into time segments and write clear, natural-language descriptions for each segment. 3. Apply labels at three levels of detail for each applicable segment: - Atomic motion (a few seconds) — a single small movement (e.g., "close fingers around the red handle") - Skill / subtask (several seconds to ~20 seconds) — a complete, meaningful action (e.g., "pick up the red block by its edge") - Task / goal (up to ~1 minute) — the overall purpose of a sequence of skills (e.g., "place all blocks in the container") 4. Ensure every moment of video is covered by a label at two or more of these levels — no gaps, including idle or pause moments. 5. Accurately describe exactly what happens, including when something doesn't go as planned (a dropped object, a failed grasp, a slipped grip). Precision matters more than making the robot look successful. 6. Cross-reference all three camera angles: use the overhead view to understand the overall scene and object identity, and the close-up wrist views to confirm exact contact and grasp details. 7. Follow a detailed style guide covering vocabulary for actions, spatial relationships, object descriptions, and manner of movement, applying it consistently across many episodes. 8. Participate in periodic calibration sessions