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Remote Ai Labeling Jobs (NOW HIRING)

Total AI

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Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

Total AI

Be Seen First

Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

Total AI

Be Seen First

Korean AI Task Contributor, Part-Time Remote

OR · Remote

$31 - $35/hr

... remote AI training projects ... Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing ...

Mercor

STEM Expert - Fully Remote

New York, NY · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research teams to close knowledge ... labeling, evaluation, or human feedback collection. * Experience with LLMs , AI systems , or ...

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Remote Ai Labeling information

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How much do remote ai labeling jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for remote ai labeling in the United States is $30.53, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $39.18 per hour, depending on experience, location, and employer.

What is remote AI labeling?

Remote AI labeling is a job where individuals annotate or tag data—such as images, videos, text, or audio—from a remote location, typically their home. This labeled data is used to train artificial intelligence and machine learning models to recognize patterns or make decisions. Tasks may include drawing bounding boxes around objects in photos, transcribing audio, or categorizing content. Remote AI labeling jobs are popular for their flexibility and are essential in industries like autonomous vehicles, healthcare, and e-commerce. No advanced technical skills are usually required, though attention to detail is important.

What are some common challenges faced by remote AI labeling specialists, and how can they be addressed?

Remote AI labeling specialists often encounter challenges such as maintaining focus during repetitive tasks, ensuring high accuracy, and managing tight deadlines. To address these, it's helpful to establish a structured work routine, use productivity tools to minimize distractions, and regularly review the labeling guidelines to avoid errors. Additionally, many companies provide collaborative platforms and regular feedback sessions, which can help clarify expectations and improve overall performance.

What are the key skills and qualifications needed to thrive as a Remote AI Labeling Specialist, and why are they important?

To thrive as a Remote AI Labeling Specialist, you need strong attention to detail, basic computer literacy, and familiarity with data annotation principles, often supported by a high school diploma or equivalent. Experience with labeling platforms, image or text annotation tools, and sometimes knowledge of data privacy standards are typically required. Being reliable, self-motivated, and able to communicate clearly helps you consistently deliver accurate work and meet deadlines. These skills ensure high-quality labeled data, which is crucial for training effective AI models.

What is the difference between Remote Ai Labeling vs Remote Data Annotation?

AspectRemote Ai LabelingRemote Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI development, machine learningData processing, machine learning
Job FocusLabeling data specifically for AI modelsAnnotating various data types for machine learning

Remote Ai Labeling and Remote Data Annotation are closely related roles in the AI industry. Both involve working remotely with data, but Ai Labeling focuses specifically on labeling data to train AI models, while Data Annotation encompasses a broader range of data types and tasks. Understanding these differences helps job seekers find roles that match their skills and career goals.

More about Remote Ai Labeling jobs
What cities are hiring for Remote Ai Labeling jobs? Cities with the most Remote Ai Labeling job openings:
What are the most commonly searched types of Ai Labeling jobs? The most popular types of Ai Labeling jobs are:
What states have the most Remote Ai Labeling jobs? States with the most job openings for Remote Ai Labeling jobs include:
What job categories do people searching Remote Ai Labeling jobs look for? The top searched job categories for Remote Ai Labeling jobs are:
Remote Ai Labeling jobs near you
Infographic showing various Remote Ai Labeling job openings in the United States as of July 2026, with employment types broken down into 5% Internship, 42% Full Time, 37% Part Time, and 16% Contract. Highlights an 100% Remote job distribution, with an average salary of $63,493 per year, or $30.5 per hour.
Korean AI Task Contributor, Part-Time Remote

Korean AI Task Contributor, Part-Time Remote

Total AI

OR • Remote

$31 - $35/hr

Part-time

Posted 8 days ago

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Job description

APPLY HERE:
https://totaltask.ai/projects/f73f5ed0efc8cebe?lang=ko&utm_source=zip_recruiter
We are looking for fluent Korean speakers to participate in remote AI training projects. Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing language-based assignments, and helping improve AI systems.

Requirements:

  • Fluent or native-level Korean
  • Strong attention to detail
  • Reliable internet connection and computer access
  • Ability to follow written instructions
  • Previous AI or data-labeling experience is helpful but not required

This is flexible, remote, project-based work. Task availability and compensation may vary by project, and all details will be shown before you begin.
APPLY HERE:
https://totaltask.ai/projects/f73f5ed0efc8cebe?lang=ko&utm_source=zip_recruiter

Company Description

Total AI is a technology company focused on building high-quality, human-generated datasets that support AI training, evaluation, and research.
Our projects may include voice recordings, language-based tasks, content review, data labeling, and response evaluation. This work helps AI systems better understand different languages, accents, communication styles, and real-world situations. We work with contributors from diverse backgrounds and provide clear instructions for every project.