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How much do ai annotator jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for ai annotator in the United States is $61.40, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $68.27 per hour, depending on experience, location, and employer.

What is an AI Annotator job?

An AI Annotator is responsible for labeling, tagging, and categorizing data used to train machine learning models. This can include annotating images, text, audio, or video to help AI systems recognize patterns and improve accuracy. The role requires attention to detail, consistency, and sometimes domain-specific knowledge. AI annotators often use specialized tools and follow predefined guidelines to ensure high-quality data labeling. Their work is essential for enhancing AI model performance across various applications.

What are the key skills and qualifications needed to thrive in the Ai Annotator position, and why are they important?

To thrive as an AI Annotator, you need keen attention to detail, strong analytical skills, and familiarity with data labeling procedures, often supported by a high school diploma or higher. Experience with annotation tools, data management systems, and sometimes basic knowledge of programming languages or machine learning concepts is highly valued. Excellent communication, the ability to follow guidelines precisely, and time management skills set top performers apart in this field. These qualifications ensure the accurate annotation of data, which is essential for effective AI model training and overall project success.

What does a typical day look like for an AI Annotator?

A typical day for an AI Annotator involves reviewing, labeling, and categorizing various data types such as images, text, audio, or video according to detailed project guidelines. You’ll frequently use specialized annotation platforms and collaborate with team leads or quality assurance members to ensure data accuracy and consistency. Some projects may require handling large data volumes or adapting quickly to updates in labeling instructions. Regular communication with developers or data scientists may also be part of the role to clarify ambiguities and enhance the quality of training data. This work is usually performed individually but often within a supportive team environment.

How to become an AI annotator?

To become an AI annotator, you typically need strong attention to detail, good reading comprehension, and basic computer skills. Many positions require no formal degree, but familiarity with data labeling tools and understanding of AI concepts can be helpful. Training is often provided by employers, and the work may involve flexible or remote schedules.

How much do AI annotators make?

AI annotators typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of annotation tasks. Many positions are freelance or part-time, requiring attention to detail and familiarity with annotation tools.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior AI researcher, machine learning director, or AI product executive. These roles often require advanced skills in data science, programming, and experience managing AI projects, and they may involve leadership responsibilities or specialized expertise. Compensation at this level reflects significant experience, impact, and industry demand.

What does an AI annotator do?

An AI annotator labels and tags data such as images, videos, or text to help train machine learning models. This role requires attention to detail and familiarity with annotation tools, often working with large datasets to ensure accurate and consistent labeling. The work supports the development of AI systems in various applications like computer vision and natural language processing.
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Ai Annotator jobs near you
Infographic showing various Ai Annotator job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $127,720 per year, or $61.4 per hour.
Generative AI Annotator - Flexible Hours

Generative AI Annotator - Flexible Hours

Innodata Inc.

Remote

$15/hr

Full-time, Part-time

Posted 10 days ago

Job description

Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
Scope of the Role:
At Innodata, we're partnering with the world's leading technology companies to build the future of generative AI and large language models (LLMs). We're on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program.
This is not a traditional full-time role. It's a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact-on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time.
You'll be helping LLMs learn the intricacies of language and reasoning-not just how to write, but how to think. If you've ever dreamed of shaping the intelligence behind tomorrow's technology, this is your chance.
This is more than just a gig-it's a rare chance to help shape the future of AI from anywhere in the world, on your own terms.
What You'll Own:
  • Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions.
  • Labeling elements of a piece of content rather than the content as a whole.
  • Assigning predefined categories or labels to items.
  • Evaluating the perceived quality and/or appropriateness of content
  • Generating labels to advance understanding of a concept, trend etc.
  • Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity.
  • Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines.
  • Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content.
  • Ordering or ranking items based on a set of preferences or criteria.
  • Creating prompts or questions that will be used to generate responses from a language model or other AI system.
  • Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.).
  • Generating responses to prompts or questions using a language model or other AI system.
  • Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines.
  • Producing concise summaries of longer pieces of text or data.
  • Converting spoken language or audio content into written text.
  • Converting text or spoken language from one language to another.
  • Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content.

You'll Thrive in This Role If You Have:
  • A Bachelor's degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master's or PhD)
  • Professional or Expert level proficiency (C1/C2) in English

The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications.
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission's guide at https://consumer.ftc.gov/articles/job-scams.
If you believe you've been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.

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