About the Role

We work with AI companies to make their models more accurate — and right now, that means basketball. Our client's AI watches game footage and automatically tags what's happening in every clip: who's shooting, what kind of shot, who has the ball, and dozens of other details. It's impressively good, but not perfect — and that's where you come in.

As a QA Reviewer, you'll watch short video clips, check what the AI got right, and correct what it got wrong. Every correction you make helps the model learn and get sharper. It's real, hands-on work on an actual AI system — not a simulation, not busywork. If you're curious about AI/ML and want to start your career doing something that actually matters, this is a great place to begin.

What You'll Do

Watch short basketball video clips (5–25 seconds each) and compare them against the AI's annotations.

Review and correct details like player identity, jersey number, shot type, and ball possession — wherever the model wasn't confident about its own answer.

Log your corrections through a QA dashboard, and flag anything genuinely unclear to your Team Lead instead of guessing.

Build up real fluency in basketball terminology and the annotation rules through structured, paid training — no basketball knowledge needed to apply.

Work as part of a small, tight-knit team with a Team Lead always around to help.

Who We're Looking For





0–2 years of experience — freshers and recent graduates are genuinely encouraged to apply.

BCA, B.Tech, BE, or a related degree — pursuing (final year) or already completed.

A sharp eye for detail — you notice the small things other people scroll past.

Comfortable spending focused time on video review and dashboard-based work.

Enthusiastic about AI/ML and genuinely excited to help make a model better, not just clock hours.

Clear written English and good communication with your team.

Reliable and punctual — able to commit to a consistent daily schedule.

Nice to Have (not required)

An interest in sports — basketball especially, though we'll train you on the game terminology regardless.

Basic comfort with spreadsheets or easy software dashboards.

Any prior exposure to data labelling, annotation, or QA-style work.

What We Offer

Competitive stipends for early-career candidates, based on experience and interview performance.

A genuinely supportive work environment with hands-on mentorship — you won't be thrown in and left alone. Working with US client.

Real exposure to how modern AI/ML products are actually built and refined.

A full, paid training period before you're expected to work independently.

How to Apply

Send your resume to [email protected] with the subject line “QA Reviewer — Jaipur.”

Tell us briefly why you're interested — we read every application ourselves.

📌 Data Annotator - QA Reviewer (Jaipur)
🏢 voiceXP
📍 Jaipur