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  • Posted: Feb 4, 2026
    Deadline: Not specified
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  • Technology has gained the ability to reason, or at least simulate it; This fundamentally changes the way we interact with technology. It is time to use this phase shift to free our builders & innovators from non mission-critical tasks - It’s time for them to focus on work only they can do. Because if we free our brightest minds from suffocating β€œb...
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    Freelance Visual Data Collector (AI Training)

    Project: Real-World Image Capture for AI Model Training
    Location: Remote / Field-Based
    Engagement Type: Freelance, On-Demand (Client-Driven Volume)
    Compensation: Pay-Per-Series

    About the Role

    We are looking for reliable, detail-oriented individuals to join our global network of Visual Data Collectors supporting AI model training.

    This role does not require professional photography experience. Instead, success in this position depends on your ability to follow detailed instructions precisely and capture authentic, real-world moments that reflect everyday life.

    Your contributions will help train AI systems to better understand lighting, perspective, depth, and environmental context using real, unedited imagery.

    How the Work Operates

    • On-Demand Projects: Work availability is based on client demand. Some periods may have higher volume than others.
    • Flexible Schedule: When projects are active, you work on your own schedule, provided deadlines are met.
    • Output-Based: Compensation is strictly tied to approved deliverables, not time spent.

    Scope of Work

    You will create photographic Series, each representing one real-world scenario.

    What is a Series?

    • One scenario captured through 5–6 required photos
    • Examples include: someone drinking coffee, fixing a light, walking in a park, or a family picnic
    • Images must look natural and unstaged

    Important Notes

    • Photos do not need to be artistic or complex
    • Accuracy, clarity, and realism are essential
    • All images must strictly follow provided technical and content guidelines

    Key Responsibilities

    • Capture authentic, believable real-life scenarios
    • Ensure correct focus, lighting, and environmental consistency
    • Organize and label images according to required metadata standards
    • Submit completed series via Google Drive
    • Obtain signed indemnity forms for all human subjects (template provided)
    • Avoid visible logos, brand names, or copyrighted materials

    Requirements

    • Equipment: Smartphone or digital camera capable of at least 7 MP images
    • Reliability: Ability to follow instructions exactly—near-correct data cannot be used
    • No Editing: Images must be raw; no filters, retouching, or AI tools permitted
    • Access: Ability to shoot in varied environments (home, streets, parks, cafés, etc.)
    • Compliance: Willingness to adhere strictly to ethical and legal data-collection standards

    Compensation & Payment Terms

    • Base Rate: $3.50 per approved Series (each Series = 5–6 photos of one scenario)
    • Pay-Per-Output: Payment is issued only for submissions that fully meet quality and guideline requirements
    • Efficiency Potential: Contributors who optimize their workflow may earn the equivalent of up to $28/hour based on approved output (not guaranteed)
    • Volume Incentives: Higher rates or bonuses may be offered to contributors who consistently submit 100+ approved series
    • No Fees: We do not charge applicants or contributors any fees at any stage

    Next Steps

    If you have:

    • A smartphone or camera
    • Access to everyday environments
    • Strong attention to detail
    • The ability to follow detailed instructions

    We encourage you to apply. Selected applicants will receive full documentation outlining file specifications, metadata requirements, and submission workflows.

    Check how your CV aligns with this job

    Method of Application

    Interested and qualified? Go to RAY AI Inc. on careers.getray.ai to apply

    Build your CV for free. Download in different templates.

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