Data Annotators: Categorize Data for AI Training

Yes. Terac is a funded, US-based marketplace with real AI-lab and market-research clients, not a task-mill. It verifies your identity and professional background before matching you to any paid work, which is stricter screening than most open task queues use.

You complete a short AI-driven interview, identity verification, and a domain-specific screening test once. After that, Terac matches verified candidates to paid studies that fit their profile instead of running an open queue, and pay is released once your submission on this listing is checked against the requirements above.

Project-based, not steady. Terac opens listings like this in bursts when an AI lab requests a specific batch, categorizing data, writing or validating coding tasks, creating expert-level problems, and closes them once the batch is filled or complete. Treat it as recurring gig income you requalify for each time, not a standing job.

Pay tracks verified expertise, not a platform-wide rate. Generalist labeling sits at a few dollars an hour; work gated behind a passed domain screening, like software engineering or STEM problem creation, pays task bounties well over $100. Check this listing's own rate above rather than assuming other Terac listings pay the same.

Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.

No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.

Tasks here are scoped to Data Science, not generic labeling. As a Data Annotators: Categorize Data for AI Training, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Data Science) rather than following a one-size-fits-all rubric. If you don't have hands-on Data Science background, this is likely not the right listing to start with.

You'll be taken to Terac's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.