If accuracy matters more to you than speed, this position will be a natural fit. The labels you create become training data for AI systems used daily by thousands of students. Precise behavioral labeling improves the product. Inconsistent labels teach the model incorrect patterns.
LearnWith.AI develops AI-powered learning experiences grounded in learning science, data analytics, and subject matter expertise. This position exists to convert raw student session videos into high-accuracy, rubric-based labels the team can rely on. You will review recorded student sessions, locate critical behavioral events, and apply rigorous rules to classify what occurred and at what timestamp. You will also evaluate LLM pre-annotations, correct errors, and document edge cases to help engineers refine the system.
This is not gig-based, random annotation work. It is a consistent queue within a single product domain, featuring direct feedback loops, calibration against gold standards, and advancement tied to accuracy and consistency. If you value clear expectations, measurable quality, and work that directly influences model performance, we would like to hear from you.
This role exists so that student session videos are transformed into ≥95%-accurate, time-precise labeled datasets that reliably indicate when model performance improves or regresses.
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.






It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.
Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.
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.