Role description
Data Labeling Intern
SwingVisionSwingVision is the AI racket sports app that provides automated stats, highlights, and line calling using just your phone. Our mission is to democratize the pro sports experience for all athletes.
Led by AI experts from Tesla & Apple, we are a small but passionate team building a category-leading consumer product and pushing the limits of what’s possible on a mobile device.
Recent achievements include:
• Apple Design Award, Editors' Choice on the App Store, and 4x App of the Day
• Featured in
Apple Keynote events
,
Forbes
,
Financial Times
&
The New York Times
• Trusted by 500k+ players, coaches, and federations all across the globe
• $10m+ raised from Sony, Tennis Australia and Andy Roddick
💼
The Role
We are currently seeking part-time Data Labelers to bring our ball-tracking A.I. to all racket sports. As a data labeler in our startup, you will work alongside our Machine Learning team in Berkeley, CA, become knowledgeable in basic computer vision concepts, and learn how a consumer artificial intelligence product is made.
🧰 Responsibilities
• Record video of tennis, pickleball, padel players on the court
• Accurately label images of tennis/pickleball/padel balls and players
• Update data labeling guidelines with edge cases and other difficult scenarios
• Provide feedback & suggestions to help improve the design of our labeling interface
• Maintain a labeling accuracy of greater than 95%
🎯 Requirements
• Agility in using a keyboard & mouse
• Deep attention to detail, quality and patience
• Thorough knowledge of tennis, pickleball, padel terminology (e.g. serviceline, baseline, doubles alley, deuce court, ad court, kitchen/NVZ, forehand, backhand, topspin, slice, etc.)
⭐️ Preferred
• Comfortability using macOS
• Passion for playing video games with a keyboard & mouse
• Avid user of the SwingVision app
• Passion for Racket Sports or Artificial Intelligence
SwingVision is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.