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AI Video Trainer - Hebrew

Remote · India Full-time

Wing Data is looking for Freelance AI Audio & Video Trainers to support one of our clients on an AI Training Audio & Video Participation Study. This is a flexible, project-based opportunity rather than a full-time or monthly position. Work is assigned based on availability, and tasks may range from a single 5-minute session to several hours of work. Language Required: Hebrew \n

What You'll Do

Record audio/video tasks that help train next-generation AI systems. Review requirements, then continue to partner onboarding. You will participate in audio/video recording tasks that may involve speaking, labeling, reviewing, or following on-screen instructions. Your submissions support the development and training of next-generation AI systems. We are collecting high-quality human data to improve how AI understands speech, behavior, communication, and real-world interactions. Follow task instructions carefully and record in a clear, accurate, and suitable environment.

Responsibilities

You must meet all of the following: 1080P Camera Phone or webcam with at least 1080p resolution (validated during onboarding). Eligible Language You speak the Hebrew language fluently (verified during onboarding). Government ID Valid government-issued ID for identity verification. Quiet Space Tasks completed in a quiet room; background noise may cause automatic audio failures. Even Lighting Face-on, natural light works well; avoid strong backlighting, shadows, or dark rooms.

Compensation

We offer a pay range of $10 - $20 per hour, with the exact rate determined based on experience, expertise, and geographic location. Final offer amounts may vary from this listed range Pay is structured around an hourly rate and prorated by task length. \n$10 - $22 an hour \n Important: While submitting your application, please complete our short screening form here: [ https://forms.gle/HauJ3djs6iYvfHgv7 ] We will ONLY review candidates who complete both the application and the screening form. The form takes about ~60 seconds to complete.

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