Remote AI Media Evaluator - Spot Flaws & Explain (Up to $15)

Outlier

Burlington (VT)

Remote

USD 17,000 - 24,000

Full time

19 hours ago
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Benefits offered by this job

Fully remote
Flexible hours
Weekly payments (ACH/PayPal/AirTM)

Job summary

Outlier is seeking detail-oriented English speakers to review AI-generated media from the comfort of home. You will hold live conversations with AI voice models, compare image and video pairs, and explain what’s off. The role is fully remote with flexible hours and pay up to $15 per hour, plus incentives.

As part of Outlier’s evaluation team, you’ll help improve AI systems by documenting what went wrong and why, supporting frontier research in a real-world context.

Qualifications

  • Fluent English speaker with strong, clear written communication.
  • Strong attention to detail and the ability to replay or zoom in to verify issues.
  • Pursuing or holding a Bachelor's degree or above.
  • Comfortable speaking about realistic situations in natural conversation.
  • Experience writing concise explanations or reviews.

Responsibilities

  • Holding a live, scenario-based conversation in English with AI voice models, then ranking how natural and clear each sounds.
  • Comparing AI-generated images and videos and judging which better follows the prompt.
  • Inspecting outputs closely to spot issues like distorted anatomy, flickering, or mismatched audio/video.
  • Writing a specific written explanation in English that points to what you saw or heard.

Skills

Fluent English
Clear written communication
Attention to detail

Education

Bachelor's degree or above

Job description

Outlier is seeking detail-oriented English speakers to review AI-generated media from the comfort of home. You will hold live conversations with AI voice models, compare image and video pairs, and explain what’s off. The role is fully remote with flexible hours and pay up to $15 per hour, plus incentives.

As part of Outlier’s evaluation team, you’ll help improve AI systems by documenting what went wrong and why, supporting frontier research in a real-world context.

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