Data Annotators: Paid Tasks for AI Model Training
Terac
Data Annotators: Paid Tasks for AI Model Training
Terac
No-code AI for unstructured data automation
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.
You will log into our remote platform to access a queue of diverse annotation assignments. Depending on the current batch, you might categorize text, highlight specific entities, or evaluate AI-generated responses for quality. You will work through these assignments independently and at your own pace. The project features rolling availability, allowing you to seamlessly fit the work around your existing schedule.
We are looking for detail-oriented individuals with prior experience in data annotation, data labeling, or AI model evaluation. We welcome freelance labelers, QA testers, content moderators, and machine learning data specialists. You must be comfortable working independently and adapting to new labeling guidelines as project parameters evolve.
Review text or media samples based on provided project guidelines
Apply accurate labels and categorizations to diverse data sets
Evaluate AI-generated responses for clarity, safety, and factual accuracy
Manage your own time to complete assignments at your preferred pace
Prior professional experience with data annotation or labeling
Strong attention to detail and ability to follow complex guidelines
Comfortable working independently on a remote basis
Familiarity with evaluating AI outputs or machine learning datasets
$40 per hour
Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.
Learn more at terac.com or on YouTube at @jointerac.
Terac provides a no-code AI platform that automates the handling of unstructured data, turning emails and documents into structured, actionable information. Users build, manage, and scale AI-driven automation for tasks like document classification, data extraction, and email processing without needing extensive AI expertise or large training datasets. Compared with traditional AI tools, Terac focuses on a no-code, end-to-end approach for unstructured data, letting teams deploy automations without coding or separate data-extraction components. Its goal is to improve operational efficiency by reducing manual, repetitive work and speeding up information processing across workflows.
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