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Data Annotation Specialist Jobs (NOW HIRING)

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models. What you'll do

Applied Intuition

Data Quality Specialist

Sunnyvale, CA · On-site

$30 - $45/hr

About the role As a Data Quality Specialist you will be a critical component of our autonomous ... Familiarity with data annotation tools and workflows * Experience with data validation techniques ...

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How much do data annotation specialist jobs pay per year?

As of Jun 8, 2026, the average yearly pay for data annotation specialist in the United States is $72,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $87,000.00 per year, depending on experience, location, and employer.

What is a data annotation specialist?

A data annotation specialist is a professional who labels and tags data such as images, text, or videos to help train machine learning models. They use tools and follow guidelines to ensure data is accurately annotated, which is essential for developing AI systems. Attention to detail and understanding of data types are important skills for this role.

What are Data Annotation Specialists?

Data Annotation Specialists are professionals who label and categorize data—such as images, text, audio, or video—to make it usable for machine learning models and artificial intelligence systems. Their work ensures that algorithms can accurately interpret data by providing clear examples of what different data points represent. Tasks may include drawing bounding boxes on images, transcribing audio, or tagging keywords in text. This role is crucial for improving the accuracy and reliability of AI applications across various industries.

What are some common challenges a Data Annotation Specialist faces, and how can they be addressed?

Data Annotation Specialists often encounter challenges such as maintaining high accuracy while labeling large volumes of data, managing repetitive tasks, and understanding complex annotation guidelines. To overcome these, it's important to stay detail-oriented, take regular breaks to avoid fatigue, and seek clarification on ambiguous instructions. Collaborating with team members and participating in quality review sessions can also help ensure consistency and improve annotation quality over time.

What is the difference between Data Annotation Specialist vs Data Labeler?

AspectData Annotation SpecialistData Labeler
CredentialsHigh school diploma or equivalent; some roles may prefer certifications in data management or annotation toolsTypically high school diploma or equivalent; minimal formal requirements
Work EnvironmentOffice or remote; often involves using specialized annotation softwarePrimarily remote or in-house; focuses on labeling data within specific datasets
Industry UsageUsed across AI, machine learning, and data science projectsPrimarily in AI and machine learning industries for training data
Job FocusInvolves detailed annotation, quality control, and understanding project guidelinesFocuses on labeling data accurately according to instructions

While both roles involve working with data to train AI models, Data Annotation Specialists typically handle more complex annotation tasks and quality assurance, whereas Data Labelers focus on straightforward labeling tasks. The Specialist role often requires a deeper understanding of project guidelines and may involve using advanced annotation tools.

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

To thrive as a Data Annotation Specialist, you need a keen attention to detail, strong analytical abilities, and basic knowledge of data labeling concepts, often supported by a high school diploma or relevant coursework. Familiarity with data annotation tools (such as Labelbox or Supervisely), basic computer skills, and sometimes an understanding of programming languages like Python are valuable. Excellent communication, time management, and the ability to follow guidelines precisely help you stand out in this position. These skills ensure accurate and consistent data labeling, which is essential for training reliable machine learning models.
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Data Annotation Specialist jobs near you
Infographic showing various Data Annotation Specialist job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $72,947 per year, or $35.1 per hour.

AI Training Specialist (Data Annotation)

Remote Talent Cloud

Chicago, IL • Remote

$20/hr

Full-time, Part-time

Posted 29 days ago

Job description

As an AI Training Specialist (Data Annotation), you’ll play a key role in helping train and improve artificial intelligence (AI) systems. Your work will directly support how AI models learn to recognize text, images, and other data accurately.

Your main responsibilities will include:

  • Labeling and categorizing data (such as text, images, or short videos) according to detailed project guidelines
  • Reviewing and verifying data for accuracy, consistency, and completeness
  • Identifying and flagging any errors, inconsistencies, or unclear data
  • Following clear annotation instructions to ensure high-quality results
  • Meeting productivity and accuracy goals within project timelines
  • Maintaining confidentiality and adhering to all data security standards

Requirements

We’re looking for detail-oriented individuals who are comfortable working independently and enjoy structured, accuracy-focused tasks. The ideal candidate will have:

  • This is a fully remote position, but you must be located within the United States
  • Excellent attention to detail and strong organizational skills
  • A reliable Internet connection and computer
  • The ability to focus for extended periods and follow detailed written instructions
  • Strong written communication skills in English
  • Previous data annotation, labeling, or transcription experience is a plus, but not required

Benefits

  • Fully remote: work from anywhere within the United States
  • Full-time and part-time available
  • Competitive hourly pay from $20/hr
  • Training provided for all annotation tools and workflows
  • Gain hands-on experience supporting real-world AI training projects
  • Be part of a growing remote team working on cutting-edge technology