Quality & Data Intern (m/f/d) – Mandatory Internship / Prácticas

Job description

About JawBuddy JawBuddy helps people with jaw pain, teeth grinding and TMJ problems through a guided exercise app. Our app measures jaw movement through the phone camera using computer vision and AR, so users see their progress in real numbers. We are a small, funded health-tech team with paying customers in Germany. Next up: a B2B platform release in early 2027. How this internship works We offer this role in exactly two ways: Mandatory internship at an EU university : you are enrolled at a university in the EU and your study regulations require an internship. You send us a document from your university that confirms this. Start as soon as possible . Prácticas at a Spanish university : you are enrolled at a university in Spain, and the internship runs through your university's internship agreement (prácticas extracurriculares with a convenio), full-time or alongside your studies. Start from December 2026 . We can't offer working-student contracts, voluntary internships or freelance work. The role You make sure our app and our numbers can be trusted, and you use AI to do it at a scale one person couldn't before. AI handles the repetitive checks; you handle what needs human judgment, like testing our camera features in the real world. You work directly with our CTO and founding engineer. About 60 % app and computer vision quality: real-world testing, releases, accessibility, performance About 25 % data quality: making sure analytics data is complete and correct About 15 % automation with AI: building automated tests and checks, and reviewing what they find What you'll do Test our computer vision in the real world Test camera-based jaw tracking across devices, lighting, faces, glasses and beards Find the conditions where measurements break, and help the team fix them Own app quality Own the release checklist for every iOS and Android build Test accessibility, German texts, performance, slow networks and offline use Write clear bug reports in Linear, with steps to reproduce and evidence Keep test evidence documented, as our product requires Keep our data trustworthy Review the daily data-quality checks across Amplitude, AppsFlyer, RevenueCat and BigQuery, and investigate what they flag Find out why two tools disagree, and get it fixed Keep our tracking plan in sync with what the app actually sends Automate with AI Use AI tools to write automated tests (Maestro…