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Text Annotator Jobs (NOW HIRING)

LILT (Production)

$20/hr

Oversee large-scale data pipelines for multilingual data collection (audio, text, image) and LLM ... Accuracy scores, Inter-Annotator Agreement (IAA), and gold-set performance. * Productivity: Cost ...

Careerflow

Japanese Data Annotator

$640/wk

Not voice-based -- text and image annotation only * No Interview, only assessment: 15-20 minute language skills assessment You will be working for Careerflow on behalf of one of our clients.

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Text Annotator information

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$28

How much do text annotator jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for text annotator in the United States is $22.63, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $25.00 per hour, depending on experience, location, and employer.

What is a text annotator?

Text Annotators are professionals who label and categorize text data to help train artificial intelligence (AI) and machine learning models. Their work involves reading documents, identifying specific elements such as entities, sentiments, or key phrases, and tagging these according to predefined guidelines. This process ensures that AI systems can accurately interpret and process human language by learning from well-labeled examples. Text annotators often work with a variety of texts, including emails, social media posts, and articles, to create high-quality datasets for natural language processing (NLP) applications.

What are the key skills and qualifications needed to thrive as a text annotator, and why are they important?

To thrive as a Text Annotator, you need strong language proficiency, attention to detail, and familiarity with linguistic concepts, often supported by a degree in linguistics, language studies, or a related field. Experience with annotation tools, text labeling platforms, and sometimes basic scripting or data management systems is typical. Excellent focus, time management, and clear communication are important soft skills in this role. These capabilities ensure the accurate and efficient preparation of high-quality annotated datasets essential for machine learning and natural language processing projects.

What are some common challenges faced by text annotators, and how can they be addressed?

Text annotators often encounter challenges such as maintaining consistency in labeling, understanding ambiguous language, and managing large volumes of data. To address these, teams typically provide detailed annotation guidelines, conduct regular training sessions, and use collaborative review processes to ensure accuracy. Utilizing annotation tools with built-in quality checks and establishing open communication with project managers can also help annotators overcome these hurdles and deliver high-quality results.

What is the difference between Text Annotator vs Data Labeler?

AspectText AnnotatorData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, NLP projectsAI, machine learning, data preparation
Search IntentCompare roles in data annotationCompare roles in data labeling

Text Annotators and Data Labelers often perform similar tasks in AI and machine learning projects, focusing on preparing data for model training. While the terms are sometimes used interchangeably, Text Annotators typically specialize in labeling text data specifically, such as identifying entities or sentiment, whereas Data Labelers may work with various data types, including images and audio. Both roles require attention to detail and familiarity with annotation tools, making them closely related but distinct in scope.

What are popular job titles related to Text Annotator jobs?

For Text Annotator jobs, the most frequently searched job titles are:

Infographic showing various Text Annotator job openings in the United States as of September 2026, with employment types broken down into 40% Full Time, 40% Part Time, and 20% Contract. Highlights an 40% In-person, and 60% Remote job distribution, with an average salary of $47,067 per year, or $22.6 per hour.

AI Trainer - Freelance Data Annotator

Austin, TX • Remote

Mindrift - Data annotation
See more jobs at Mindrift - Data annotationexternal

$20/hr

Part-time

Re-posted 23 days ago

Job description

Please submit your resume in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

What this opportunity involves

Annotation is what helps AI make sense of the world. As an annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses - when projects are available.

While each project involves unique tasks, contributors may:

  • Carefully review provided data (text, images, or videos);
  • Label or classify content based on project guidelines;
  • Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.

What we look for

This opportunity is a good fit for candidates open to part-time, non-permanent projects. Ideally, contributors will have:

  • Bachelor's degree in any discipline;
  • Minimum 1 year of experience in any professional role;
  • Logical thinking, fact-checking and reasoning abilities;
  • Strong attention to detail and ability to understand and follow complex instructions;
  • Strong communication skills, including the ability to ask clarifying questions when needed;
  • Genuine interest in technology and artificial intelligence;
  • Strong written and spoken English (C1+).

How it works 

Apply Pass qualification(s)  Join a project (when available) Complete tasks Get paid

Why this freelance opportunity might be a great fit for you

  • Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments;
  • Participate into advanced AI projects and gain valuable experience that enhances your portfolio;
  • Influence how future AI models understand and communicate in your field of expertise.

Project time expectations

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.

Compensation

Paid per accepted task. Your rate depends on the qualification tier you reach and how efficiently you complete tasks - up to the equivalent of $20/hr. Because payment is per task, a faster pace raises your effective hourly rate. Keep in mind, quality standards must be maintained, regardless of speed.

Apply