Vision-Language-Action (VLA) Annotator

CNTXT AI; Philippines; Remote; PHP 240,000 - 360,000; Full time

Job summary

CNTXT AI is seeking detail-oriented VLA Annotators in the Philippines to support high-quality training data for Vision-Language-Action and robotics models. You will review videos, segment actions with precise timing, and craft clear descriptions of on-screen activities.

You will validate AI-generated captions and ensure consistency and accuracy across annotations. Ideal candidates have strong attention to detail, excellent written English, and the ability to follow complex guidelines.

Qualifications

• Strong attention to detail and ability to follow detailed written guidelines.
• Excellent written English with clear, concise action descriptions.
• High observational accuracy to distinguish small differences in actions and timing.
• Experience reviewing and editing video annotations or captions preferred.
• Comfort with repetitive tasks while maintaining accuracy and consistency.

Responsibilities

• Review videos and understand the task or activity being performed.
• Divide videos into action-based segments with accurate start/end times.
• Ensure all meaningful actions are captured without gaps or overlaps.
• Review and edit AI-generated captions for accuracy and clarity.
• Describe actions using simple, precise language based on visible evidence.
• Highlight relevant hands, objects, tools, and locations when needed.
• Maintain consistent terminology throughout each annotation.
• Identify invalid or unusual portions of videos per guidelines.
• Review completed work for segmentation, caption accuracy, grammar, and completeness.

Skills

Attention to detail

Guidelines comprehension

Strong written English

Observational skills

Video review

Repetitive annotation

Computer proficiency

Independence

Reliability

Feedback openness

Tools

Annotation platforms

AI-assisted labeling tools

Job description

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.