We are looking for detail-oriented VLA Annotators to support the creation of high-quality training data for Vision-Language-Action and robotics models.
Annotators will review videos of people performing real-world activities, divide them into meaningful action segments, and create or validate clear descriptions of the actions taking place. The role also involves reviewing AI-generated annotations, correcting inaccuracies, and ensuring the final data meets project-specific quality standards.
Projects may include household, workplace, industrial, manipulation, navigation, and other real-world activities.
Responsibilities
• Review videos and understand the overall task or activity being performed.
• Divide videos into logical action-based segments with accurate start and end times.
• Ensure all meaningful actions are captured without unnecessary gaps or overlaps.
• Review AI/VLA-generated captions and select, edit, or replace them when necessary.
• Write clear and concise action descriptions based only on what is visibly happening in the video.
• Accurately describe relevant hands, objects, tools, movements, and locations when required.
• Maintain consistent terminology for objects and actions throughout each annotation.