Data Annotators: Paid Tasks for AI Model Training
We are running a paid project focused on generating high-quality labeled data for artificial intelligence models.
- Pay
- Firm hourly pay: $40 per hour
- Location
- Remote
- Eligibility
- Remote, applicant location not specified
- Qualification difficulty
- Selective
How current is this information?
The public role and application path were checked. Details can still change; this is not an endorsement or guarantee.
- Platform
- Terac
- Fit category
- General professional
- Listing/source checked
- Sep 28, 2026
- Apply link checked
- Sep 28, 2026
Application
Continue to the current Terac listing
Apply on TeracOpens the current Terac page in a new tab. This may be a referral link, and Specialist AI Work may be paid if the platform credits it. That does not change the role's advertised pay or how roles are ordered here.
What this role involves
We are running a paid project focused on generating high-quality labeled data for artificial intelligence models. This ongoing initiative helps refine machine learning systems across a variety of formats and subject matters. Your work directly contributes to improving model accuracy, safety, and reasoning capabilities.
Before you apply
Review the main fit signals and unresolved details before opening the platform.
Why it may fit
- Prior professional experience with data annotation or labeling
- Strong attention to detail and ability to follow complex guidelines
Check before applying
Reasons to pause
- The current Terac opportunity no longer appears in the complete public inventory
- You cannot meet the role-specific eligibility, screening, or availability requirements
Still to verify
- Review the current Terac opportunity before applying. Opportunities can be hourly, one-time, task-based, or otherwise project-specific, and closing dates, interview capacity, time commitments, pay, screening, and availability can change.
- Applicant eligibility still needs checking: Remote, applicant location not specified.
What to prepare
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Requirements
- Familiarity with evaluating AI outputs or machine learning datasets
Best for
- Familiarity with evaluating AI outputs or machine learning datasets