Video Annotator

$30,000 USD/year ^{Pay is set based on global value, not the local market. Most roles = hourly rate x 40 hrs x 50 weeks}  ($15 USD/hour)

• Annotate student session videos by identifying, classifying, and timestamping behavioral events using a detailed rubric
• Review and correct LLM pre-annotations by removing false positives, adding missed events, and tightening timestamps
• Write clear reasoning notes for non-obvious calls, including rubric references and the assumptions you used
• Log edge cases and clarification questions for ambiguous scenarios and keep an annotation tracker updated with session metadata
• Complete calibration exercises, absorb QA feedback, and apply rubric updates to improve accuracy over time

• Build AI models, run experiments, or do research on student behavior
• Design the annotation rubric or redefine category definitions based on personal interpretation
• Optimize for speed at the cost of accuracy, consistency, or timestamp precision
• Do one-off, random tasks across unrelated domains with no context or quality loop

This role exists so that student session videos are converted into ≥95%-accurate, time-precise labeled datasets that reliably signal when model performance improves or regresses.

• At least 1 year of experience in data annotation, content moderation, QA evaluation, or similar rubric-driven review work
• Strong English reading comprehension and the ability to follow complex written instructions without drifting from the rules
• Ability to sustain focus and accuracy for 4–6 hours of video-based work per day
• Ability to spot subtle visual and on-screen behavioral cues and classify them consistently across many sessions
• Strong written documentation skills for explaining edge cases, assumptions, and clarification questions
• Reliable internet connection capable of streaming video
• Comfort reviewing, correcting, and supplementing AI/LLM-generated annotations