Data · Established · Beginner

Data Annotator / AI Trainer

Labels data and rates model outputs, producing the ground truth and preference signals models learn from.

What Data Annotator / AI Trainer is

Work ranges from straightforward labelling to expert review by clinicians, lawyers or engineers, and increasingly to ranking model responses for preference tuning.

How it works

Annotators follow detailed guidelines, meet agreement thresholds and adjudicate ambiguous cases. Domain expertise commands substantially better terms than general labelling.

Why it matters

Model quality is capped by label quality, and expert annotation is now a recognised specialist niche rather than commodity work.

Common uses

→Preference data for alignment
→Expert domain labelling
→Model output evaluation
→Safety category labelling

Strengths

✓Accessible entry point into AI work
✓Remote and flexible

Watch for

✓Exposure to distressing content in some safety work
✓Variable pay and conditions

Continue exploring

Data Labeling Reinforcement Learning from Human Feedback Annotation platforms LLM Evaluation