Remote AI Quality Evaluator — Flexible Hours

Outlier; Bozeman (MT); Remote; USD 20,000 - 29,000; Full time

Benefits offered by this job

Flexible hours

Weekly payments

Free access to leading LLMs

Higher earnings with Missions

Job summary

Outlier is seeking detail-oriented English speakers to review AI-generated media. You will roleplay live conversations with an AI voice model, score exchanges, and explain what’s off, all remotely and on your own schedule.

Join Outlier to help shape how advanced AI systems reason and learn, contributing to improvements in AI performance for real-world use cases through evaluation and feedback loops.

Qualifications

• Fluent English with clear written communication.
• Attention to detail and ability to replay or zoom in on content.
• Bachelor's degree or higher (nice to have).
• Ability to think on feet and discuss realistic scenarios naturally.
• Experience writing concise, evidence-based reviews.
• Ability to decide clearly when options have flaws.

Responsibilities

• Holding a live, scenario-based conversation in English with AI voice models, then ranking how natural, useful, and clear each one sounded.
• Comparing pairs of AI-generated images and videos and judging which one better follows the prompt.
• Inspecting outputs closely, including zooming in and replaying, to spot problems like distorted anatomy, flickering or unnatural motion, text errors, and audio that doesn't match the video.
• Rating each output across dimensions like adherence, quality, and realism, then writing a specific explanation in English that points to what you saw or heard.

Skills

Fluent English

Attention to detail

Conversational skills

Writing experience

Decision making under uncertainty

Education

Bachelor's degree or above

Job description

Outlier is seeking detail-oriented English speakers to review AI-generated media. You will roleplay live conversations with an AI voice model, score exchanges, and explain what’s off, all remotely and on your own schedule.

Join Outlier to help shape how advanced AI systems reason and learn, contributing to improvements in AI performance for real-world use cases through evaluation and feedback loops.