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Data Annotator Jobs (NOW HIRING)

Mercor

Data Annotator

New York, NY · Remote

$50/hr

Prior experience as a CB / reviewer / rater in human data or AI training pipelines . * Proven ability to follow nuanced instructions without deviation. * Strong written communication and reasoning ...

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

We are looking for Language Data Annotators to support the improvement of AI-generated content in English . Job Type: Freelance Location: Texas, work from home Work Schedule: Part-time - 10+ hours ...

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

We are looking for Language Data Annotators to support the improvement of AI-generated content in English . Job Type: Freelance Location: Texas, work from home Work Schedule: Part-time - 10+ hours ...

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$46K

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$243.5K

How much do data annotator jobs pay per year?

As of Jun 7, 2026, the average yearly pay for data annotator in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are Data Annotators?

Data Annotators are professionals who label or tag data such as images, text, audio, or video to prepare it for use in machine learning and artificial intelligence (AI) models. Their work is crucial because accurately labeled data helps algorithms learn to recognize patterns and make decisions. Data annotators may use specialized software tools to highlight objects, transcribe speech, or classify documents according to specific guidelines. The quality and accuracy of their annotations directly affect the performance of AI systems.

What is the difference between Data Annotator vs Data Labeler?

AspectData AnnotatorData Labeler
Required CredentialsHigh school diploma or equivalent; some roles may prefer basic technical skillsSimilar; often requires only basic education and attention to detail
Work EnvironmentRemote or office-based; working with datasets and annotation toolsPrimarily remote; focused on labeling data for machine learning
Industry UsageUsed across AI, machine learning, and data science industriesCommonly used in AI and machine learning sectors for training data
Search & Comparison IntentOften compared due to similar tasks and roles in data preparation

Both Data Annotators and Data Labelers perform data preparation tasks for AI models, often with overlapping skills and work environments. The main difference lies in terminology used by employers or platforms, but their roles are largely similar, focusing on labeling data to improve machine learning algorithms.

What are the typical challenges Data Annotators face when working with large datasets, and how can they overcome them?

Data Annotators often encounter challenges such as repetitive tasks, maintaining high accuracy, and dealing with ambiguous data points when working with large datasets. To overcome these, it's important to follow clear annotation guidelines, regularly communicate with team leads or project managers about uncertainties, and leverage quality control tools provided by the organization. Collaborating with peers and participating in review sessions can also help ensure consistency and improve the overall quality of the annotations.

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

To thrive as a Data Annotator, you need attention to detail, accuracy, and a basic understanding of data structures, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools like Labelbox or Supervisely, and sometimes basic coding skills are typically required. Strong organizational skills, patience, and the ability to follow precise guidelines make someone stand out in this position. These skills and qualities are crucial for producing high-quality datasets that drive effective machine learning and AI model development.
More about Data Annotator jobs
What cities are hiring for Data Annotator jobs? Cities with the most Data Annotator job openings:
What are the most commonly searched types of Data Annotator jobs? The most popular types of Data Annotator jobs are:
Who are the top companies hiring for Data Annotator jobs? The top employers for Data Annotator jobs are:
What states have the most Data Annotator jobs? States with the most job openings for Data Annotator jobs include:
What job categories do people searching Data Annotator jobs look for? The top searched job categories for Data Annotator jobs are:
Data Annotator jobs near you
Infographic showing various Data Annotator job openings in the United States as of May 2026, with employment types broken down into 18% Internship, 64% As Needed, and 18% Nights. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Video Data Annotator - Contract

Hooglee

San Francisco, CA • On-site

$25/hr

Part-time

Posted 2 days ago

Job description

Video Data Annotator (Contract) - On-Site
Location: San Francisco, On-site
Compensation: $25/hour
Schedule: Part-time (4-8 hours per day)
Duration: 10-week engagement to start
We are looking for a Video Data Annotator (Contract) to support our AI Team.
This is an on-site role. A device will be provided in the office.
Program Overview
  • 10-week initial engagement
  • Opportunity to transition to full-time based on team needs and performance
What You'll Do
  • Watch and annotate video data across different formats
  • Label and evaluate video content with high accuracy
  • Provide feedback on video quality and questionnaire setup to the AI Team
  • Communicate clearly about edge cases, inconsistencies, or improvements
Must-Have Qualifications
  • Strong attention to detail
  • Strong English reading, writing, and speaking skills
Nice-to-Have
  • Prior data labeling or annotation experience

If you're detail-oriented, comfortable working with video content, and excited to contribute to AI model development, we'd love to hear from you.

Apply