Remote AI Response Evaluator - Entry Level

Outlier

Flagstaff (AZ)

Remote

USD 20,000 - 29,000

Part time

15 hours ago
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Benefits offered by this job

Free access to leading LLMs
Weekly payments via ACH/PayPal/AirTM

Job summary

Outlier invites detail-oriented English speakers to review AI-generated media from home. You will engage in live conversations with AI voice models, score exchanges, and explain what looked or sounded off in writing. Remote, flexible hours, with weekly payments and access to leading LLMs.

Responsibilities include evaluating images, videos, and captions for adherence to prompts, quality, and realism, then providing precise, evidence-based feedback to help improve AI systems.

Qualifications

  • Fluent English with clear written and spoken communication.
  • Strong attention to detail and ability to replay or zoom in on content.
  • Comfortable discussing realistic scenarios in natural conversation.
  • Experience writing concise, evidence-based reviews.
  • Eligible from listed countries: Australia, Canada, Ireland, United Kingdom, United States.

Responsibilities

  • Hold live, scenario-based conversations in English with AI voice models and rate naturalness, usefulness, and clarity.
  • Compare AI-generated images and videos to judge how well they follow prompts.
  • Inspect outputs closely, zoom and replay to spot issues like distortion, flicker, or audio/video misalignment.
  • Write English explanations describing what you observed.

Skills

Fluent English
Attention to detail
Clear written communication
Verbal reasoning

Education

Bachelor's degree or above

Job description

Outlier invites detail-oriented English speakers to review AI-generated media from home. You will engage in live conversations with AI voice models, score exchanges, and explain what looked or sounded off in writing. Remote, flexible hours, with weekly payments and access to leading LLMs.

Responsibilities include evaluating images, videos, and captions for adherence to prompts, quality, and realism, then providing precise, evidence-based feedback to help improve AI systems.

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