Remote: AI Content Evaluator & Feedback Specialist

Scale AI; Cambridge; Remote; CAD 24,000 - 34,000; Part time

Benefits offered by this job

Flexible schedule

Free access to leading LLMs

Join 900K+ Outlier Experts

Job summary

Outlier, an AI training platform owned by Scale AI, seeks detail-oriented English speakers to review AI-generated media and rate exchanges in live conversations with AI voice models. You will compare AI outputs, judge adherence to prompts, and explain issues in writing, all on your own schedule.

The role supports remote, freelance work with pay per hour and weekly payouts. This opportunity welcomes applicants from Canada, with a focus on careful, evidence-based feedback to help improve AI

Qualifications

• Fluent English with clear written communication.
• Strong attention to detail and ability to replay or zoom in when needed.
• Capable of thinking on your feet and discussing realistic scenarios.
• Experience writing concise, evidence-based explanations or reviews.

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 adherence to prompts and quality.
• Inspect outputs closely to identify issues like distorted visuals, flickering, or misaligned audio.
• Write specific explanations in English highlighting what you observed or heard.

Skills

Fluent English

Attention to detail

On-the-fly thinking

Evidence-based writing

Clear decision making

Bachelor’s degree (nice to have)

Education

Bachelor’s degree or above

Job description

Outlier, an AI training platform owned by Scale AI, seeks detail-oriented English speakers to review AI-generated media and rate exchanges in live conversations with AI voice models. You will compare AI outputs, judge adherence to prompts, and explain issues in writing, all on your own schedule.

The role supports remote, freelance work with pay per hour and weekly payouts. This opportunity welcomes applicants from Canada, with a focus on careful, evidence-based feedback to help improve AI