Guide · Updated August 2026
Data annotator salary (2026)
There is no single data annotator salary. Pay is almost always hourly (sometimes per task), posted as a band, and only real after you pass an assessment. The figures below are the kind of ranges that appear on this board, not a government wage survey and not an offer.
Ranges we typically list
| Type of work | Listed band | Notes |
|---|---|---|
| Entry content / policy review | $12 to $20 / hr | High volume, heavy QA, often global remote |
| General data annotation (NLP, multilingual) | $15 to $25 / hr | Language skill and following instructions matter more than ML knowledge |
| Vision & language annotation | $18 to $30 / hr | Common on large platforms; US remote roles can sit higher |
| LLM writing / trainer work | $20 to $40 / hr | You produce or heavily edit text at model quality |
| RLHF / reasoning evaluation | $25 to $50 / hr | Preference data and justifications; see the RLHF guide |
| Senior or on-site specialist QA | $45 to $70 / hr | Example: autonomous vehicle QA in an office |
Source: compensation fields on listings we publish, including demo and live feed roles. Always open the job page for the number attached to that opening. How we source pay.
What actually moves the rate
- Task type. Drawing boxes is not the same job as writing a better math solution. RLHF jobs and evaluator jobs usually sit above generic labeling.
- Location rules. US-only remote often pays more than global remote because of data residency and labor rules. Remote listings still need you to read the location line.
- Domain. Law, medicine, and real software engineering screens filter the pool. Fake résumé keywords usually die in the assessment, not at the pay banner.
- QA survival. The listed ceiling is irrelevant if you are paused in week two. Read how assessments work.
Contractor reality
Most of this market is contractor or gig work: no guaranteed hours, projects that end, and unpaid or lightly paid assessments. Compare platforms on Scale AI vs Surge AI before you optimize for a headline hourly rate. Taxes, equipment, and idle time between projects are your problem, not the job card’s.
New to the field? Start with how to become a data annotator, then apply from the live feed.