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Vision-Language-Action (VLA) Annotator

Cntxt AIApplies on LinkedInData & Analytics
Hiring from
Egypt
Work type
Remote
Posted
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Vision-Language-Action (VLA) Annotator

Location: Remote

Type: Full-time / Contract


About the role

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.
  • Identify invalid, idle, distracted, failed, recovery, or otherwise unusual portions of a video according to project guidelines.
  • Review completed annotations for segmentation, caption accuracy, grammar, consistency, and completeness before submission.
  • Follow project-specific annotation guidelines and adapt quickly when requirements change.
  • Flag ambiguous examples, recurring model errors, edge cases, or unclear instructions to the Operations/Quality team.
  • Use annotation shortcuts and AI-assisted tools efficiently while maintaining required quality and productivity targets.
  • Participate in calibration, training, and feedback sessions as needed.


Requirements


  • Strong attention to detail.
  • Ability to understand and consistently apply detailed written guidelines.
  • Good written English and the ability to describe actions clearly using simple, precise language.
  • Strong observational skills and ability to distinguish small differences in actions, objects, and timing.
  • Comfortable reviewing video content for extended periods.
  • Ability to perform repetitive annotation work while maintaining accuracy and consistency.
  • Basic computer proficiency and ability to learn new annotation platforms quickly.
  • Ability to work independently and meet defined quality and productivity targets.
  • Reliable computer and internet connection.
  • Openness to feedback and ability to quickly incorporate guideline changes.


Nice to have


  • Previous experience in data annotation, video annotation, quality assurance, robotics data, computer vision, or AI training data.
  • Experience working with temporal segmentation or action recognition tasks.
  • Familiarity with AI-assisted labeling tools or reviewing model-generated outputs.
  • Experience with egocentric / first-person video data.
  • Basic familiarity with robotics, manufacturing, household tasks, or other physical-world activities.


What success looks like


  • Accurate segmentation of real-world actions.
  • Clear, self-contained, and consistent captions.
  • Minimal missed actions, unnecessary segments, or timing errors.
  • Strong judgment when reviewing AI-generated annotations.
  • Consistent quality across large volumes of video.
  • Ability to identify recurring annotation or model issues rather than treating every task in isolation.

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