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Egocentric Video Data Contributor

Perle SystemsUnited States, Puerto Rico + 9 morePosted 1 day ago

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About PerlePerle is an AI infrastructure company building expert-driven training data, evaluation systems, and applied AI products for the world's leading labs and enterprises. Headquartered in San Francisco with experts across more than forty markets, we specialize in the work that requires real human judgment: domain expertise, linguistic nuance, and cultural fidelity that generic data vendors cannot deliver.

Imagine earning extra money without changing a thing about your day. No second shift, no commute, no time away from the work or the life you already have. You film what you are already doing, and you get paid for it.

Perle is building the data that teaches AI and robotics how real people move, work, and get things done. To do that, we need video recorded from a first-person point of view: the world as you see it, through a small camera mounted on a lightweight headstrap. We are looking for contributors across the US, Canada, and Latin America to capture everyday footage and turn their ordinary routines into real income.

What You'll Actually Be DoingThe role is simple: you wear a headstrap with your phone, press record, and go about your day. The footage is captured hands-free from your perspective, so you can keep both hands on whatever you are doing.

Contributors record everyday activities and real work. That includes things like:

Household life: doing tasks around the house, cooking, cleaning, organizing, repairs, and other daily routines.

On the job: filming while you do your actual job, whether you work in manufacturing, roofing, construction, a restaurant kitchen, a warehouse, or any other hands-on trade.

Everyday activities: the small, ordinary moments that make up a normal day, captured naturally as they happen. There is no script and no acting. The whole point is authentic, real footage of real life. If you can do your job and your daily tasks, you can do this.

Why This Is Worth Your Time

Earn while you already work: Record while you work or while you handle things at home. Your day does not change; you just capture it.

Total flexibility: There are no fixed shifts. You decide when to record and how much. The more quality footage you submit, the more you earn.

Real, steady income: Pay is competitive and varies by region. You are compensated for every hour of accepted footage you deliver.

We cover your gear: Perle provides a budget to purchase the headstrap you need to get started, so the equipment is covered.

Be part of the future: The work you submit helps train the next generation of AI and robotics. Your everyday routine becomes part of something much bigger. What You'll Need

Location: You must be based in the United States, Canada, or a Latin American country. This role is open to these regions only.

Age: You must be 18 years or older.

A supported phone: You need one of the following: iPhone 11 or newer, Google Pixel 6 or newer, or Samsung Galaxy S21 or newer. A supported phone is required to capture footage.

Willingness to wear a headstrap: You should be comfortable wearing a lightweight headstrap while you work or move around the house. Perle provides a budget so you can purchase one.

Around 10 hours a week: A minimum of 10 hours of recorded footage per week is preferred. You are free to record more, and consistency helps you earn more. How It WorksStep 1 Apply and get approved

Submit your application and confirm you have a supported phone. Once you are approved, we will get you set up.

Step 2 Get your headstrap

We provide a budget to purchase the headstrap. You mount your phone, and you are ready to record hands-free.

Step 3 Record your day

Press record and go about your work and your routine. Capture at least 10 hours of footage a week, on your own schedule.

Step 4 Submit and get paid

Upload your footage through the app. Once it is reviewed and accepted, you are paid for every hour delive...

Apply now

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About Perle Systems

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AI training-data company that collects speech recordings and audio transcriptions from contributors worldwide for speech recognition models.

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