Data 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)

• Label student session recordings by detecting, categorizing, and timestamping behavioral events according to a comprehensive rubric
• Audit and refine LLM pre-annotations by eliminating false positives, capturing overlooked events, and adjusting timestamps for precision
• Document reasoning for ambiguous decisions, including rubric citations and the logic applied
• Track edge cases and clarification requests for unclear scenarios and maintain an annotation log with session metadata
• Participate in calibration sessions, integrate QA feedback, and adapt to rubric revisions to enhance accuracy consistently

• Develop AI models, conduct experiments, or perform research into student behavior patterns
• Create the annotation rubric or alter category definitions based on subjective judgment
• Prioritize speed over accuracy, consistency, or timestamp exactness
• Handle sporadic, disconnected tasks across unrelated fields without structure or quality feedback

This role ensures that student session recordings are transformed into ≥95%-accurate, time-precise labeled datasets that dependably indicate when model performance advances or declines.

• 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