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Data Annotator Jobs (NOW HIRING)

Obvio Inc

Video Data Annotator

Salt Lake City, UT · On-site

$22 - $24/hr

This role is not a typical data entry position. We are looking for candidates who can critically analyze video footage, accurately identify traffic incidents, and provide actionable data. Your ...

Prointegrate LLC

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Business Analyst - Data Annotator (USA) - Remote

Dallas, TX · Remote

$15 - $17/hr

Business Analyst - Data Annotator Location: Remote - United States Employment Type: Short-Term Contractor / Freelancer Engagement : Approximately 6-7 months (24-28 weeks) Start Date: September 4, ...

Careerflow

Japanese Data Annotator

$640/wk

Job Title We are looking for native or fluent language speakers to help train AI systems by reviewing and annotating content in their language. This is a long-term, remote gig. No prior experience is ...

Thinkfind

Image Annotator

Fort Worth, TX · Remote

$22.90/hr

The Image Annotator (also known as a Defect Annotator) is responsible for reviewing and analyzing ... Team members use data-driven processes to locate and review images containing defects of interest ...

TEKsystems

Data Annotation Specialist

Seattle, WA · Remote

$20/hr

As a Data Annotator, you will play a crucial role in improving the performance and accuracy of our AI models by providing high-quality annotated data. Psychology Degree is a huge plus! What You Will ...

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Data Annotator information

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$243.5K

How much do data annotator jobs pay per year?

As of Sep 2, 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 is a data annotator?

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 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.

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 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.

How much does a data annotator make?

Data annotators typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Some positions may offer freelance or part-time work with variable pay rates, and proficiency with annotation tools can influence earning potential.

What exactly does a data annotator do?

A data annotator labels and tags data such as images, text, or audio to help machine learning models understand and learn from the data. This role involves using specialized tools and requires attention to detail to ensure accuracy, often working with large datasets on flexible schedules.
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Data Annotator jobs near you
Infographic showing various Data Annotator job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

AI Trainer - Freelance Data Annotator

Mindrift - Data annotation

New York, NY • Remote

$20/hr

Part-time

Re-posted 16 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