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
Description
If precision matters more to you than speed, this position is built for you. The labels you create feed AI systems that support thousands of students daily. Accurate behavioral tagging sharpens the product. Inconsistent labels teach the model incorrect patterns.
LearnWith.AI develops AI-driven learning tools powered by learning science, data analytics, and domain experts. This position transforms raw student session recordings into dependable, rubric-based labels the team relies on. You will review recorded student sessions, pinpoint critical behavioral moments, and follow strict protocols to classify actions and timing. You will also audit LLM pre-annotations, correct inaccuracies, and flag edge cases to help engineers refine the system.
This is not scattered, freelance-style annotation work. It is a structured workflow within one product area, featuring direct feedback, calibration against reference standards, and advancement tied to accuracy and reliability. If you value transparent expectations, quantifiable quality, and contributions that directly shape model outcomes, we should connect.
What you will be doing
- Review student session recordings by pinpointing, categorizing, and timestamping behavioral events according to a comprehensive rubric
- Audit and refine LLM pre-annotations by eliminating false positives, inserting overlooked events, and sharpening timestamp accuracy
- Document clear reasoning for ambiguous decisions, including rubric citations and the logic behind your choices
- Record edge cases and clarification requests for unclear scenarios and maintain an annotation log with session metadata
- Participate in calibration exercises, integrate QA feedback, and implement rubric revisions to boost accuracy over time
What you will NOT be doing
- Develop AI models, conduct experiments, or perform research into student behavior
- Create the annotation rubric or reinterpret category definitions based on personal judgment
- Prioritize speed over accuracy, consistency, or timestamp precision
- Handle ad-hoc, disconnected tasks across unrelated fields without context or quality feedback
Key responsibilities
This role ensures that student session recordings are transformed into ≥95%-accurate, time-precise labeled datasets that reliably indicate when model performance advances or declines.
Candidate requirements
- Minimum 1 year of experience in data annotation, content moderation, QA evaluation, or comparable rubric-based review roles
- Excellent English reading comprehension and the capacity to adhere to detailed written instructions without deviating from established rules
- Capacity to maintain focus and precision during 4–6 hours of video-based tasks daily
- Skill in detecting subtle visual and on-screen behavioral signals and applying them uniformly across multiple sessions
- Excellent written documentation abilities for clarifying edge cases, assumptions, and questions requiring guidance
- Dependable internet connection suitable for streaming video content
- Confidence reviewing, correcting, and enhancing AI/LLM-generated annotations
Applying for a role? Here’s what to expect.
Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.
Chat-style
screening interview.
Cognitive 
aptitude test.
Prove real-world 
job skills.
Interview with the hiring manager.
Pass
proctored test.
Accept job offer.
Frequently asked questions
Reviews
Meet some people who've landed similar jobs
Recruitment sucks. So we’re fixing it.
The Olympics of work
It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.
Premium pay for premium talent
Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.
Shortlist by skills, not bias
We don’t care where you went to school, what color your hair is, or whether we can pronounce your name. Just prove you’ve got the skills.
Join the world's largest community of 
AI-first remote workers.