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Freelance Data Annotation Specialist Jobs (NOW HIRING)

Dyna Robotics

Data Annotation Specialist

As a Data Annotation Specialist, you will be pivotal in iterating on our AI system by annotating data on various tasks performed by robots, directly influencing the performance of robotic arms.

NEURA Robotics

$70 - $90/hr

Your mission & challenges As an AI Data Annotation Specialist, you will operate at the intersection of data ingestion, processing, and machine learning. Your primary responsibility is to design and ...

TEKsystems

Data Annotation Specialist

Seattle, WA · Remote

$20/hr

Use annotation tools to mark up text, images, or other data according to specific guidelines. Participate in the validation and quality assurance of annotated data to ensure it meets the required ...

CaseGuard

Data Annotation Specialist

Arlington, VA · On-site

$40K - $50K/yr

Perform accurate data entry and data validation to ensure high-quality datasets. * Review, label, and categorize images to support machine learning and AI model training. * Follow detailed annotation ...

CaseGuard

Data Annotation Specialist

Arlington, VA

$40K - $50K/yr

Perform accurate data entry and data validation to ensure high-quality datasets. * Review, label, and categorize images to support machine learning and AI model training. * Follow detailed annotation ...

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How much do freelance data annotation specialist jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for freelance data annotation specialist in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

What does a freelance data annotation specialist do?

A Freelance Data Annotation Specialist is responsible for labeling, tagging, or categorizing data—such as images, text, or audio—to help train artificial intelligence and machine learning models. They work independently, often on a contract basis, for organizations that require large annotated datasets. Their tasks may include identifying objects in photos, transcribing spoken words, or classifying text according to specific criteria. This work is essential for improving the accuracy and performance of AI systems. Freelance specialists must pay close attention to detail and follow specific guidelines to ensure high-quality annotations.

What are the key skills and qualifications needed to thrive as a freelance data annotation specialist, and why are they important?

To thrive as a Freelance Data Annotation Specialist, you need strong attention to detail, proficiency in data labeling concepts, and a foundational understanding of data privacy and security. Familiarity with annotation tools like Labelbox, Supervisely, or CVAT, and sometimes basic knowledge of Python or data formats (e.g., JSON, CSV) is often required. Being reliable, self-motivated, and able to follow complex guidelines distinguishes top performers in remote, independent work environments. These skills ensure high-quality, accurate datasets that are essential for training reliable machine learning models.

What are some common challenges faced by freelance data annotation specialists, and how can they be managed?

Freelance Data Annotation Specialists often encounter challenges such as maintaining consistent data quality, meeting tight deadlines, and understanding complex annotation guidelines from clients. It's important to develop strong time management skills and clarify instructions with clients before starting a project. Additionally, using annotation tools efficiently and staying updated on best practices can help ensure accuracy and efficiency in your work.

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

AspectFreelance Data Annotation SpecialistData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible freelance projectsRemote or on-site, often part-time or full-time
Employer/IndustryTech companies, AI/ML firms, freelance platformsTech companies, AI/ML teams, often in-house or outsourced

Freelance Data Annotation Specialists and Data Labelers perform similar tasks involving labeling data for machine learning. The main difference lies in the scope and flexibility: Freelance Specialists often work independently on varied projects, while Data Labelers may be employed full-time or part-time within organizations. Both roles require attention to detail and basic technical skills, but Freelance Data Annotation Specialists typically have more flexibility and diverse project experience.

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Freelance Data Annotation Specialist jobs near you
Infographic showing various Freelance Data Annotation Specialist 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 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $42,098 per year, or $20.2 per hour.

Operations & Data Annotation Specialist

Avanciers Inc.

Cupertino, CA • On-site

Other

Posted 4 days ago

Job description

Avanciers is a premier IT Staffing/Consulting organization and we are currently recruiting for a Contract role for one of our premier client in USA for Operations & Data Annotation Specialist


Role: Operations & Data Annotation Specialist

Location: Los Angeles, CA / San Diego, CA / Cupertino, CA


Position Summary

The Operations & Data Annotation Specialist will support data annotation and validation workflows by assisting with QA audits, annotation tool configuration, task tracking, test-plan execution, and operational reporting. The role requires strong attention to detail, process compliance, and coordination with cross-functional teams.

Key Responsibilities

  • Support data annotation and validation operations according to defined processes and guidelines.
  • Perform QA audits and review annotation quality for accuracy and consistency.
  • Configure and maintain annotation tools and task workflows.
  • Track annotation tasks, priorities, issues, and completion status.
  • Support test-plan execution and document results, defects, and observations.
  • Prepare operational and quality reports for project stakeholders.
  • Identify process gaps and escalate quality or operational issues.
  • Coordinate with data, QA, engineering, and operations teams to resolve workflow issues.
  • Maintain accurate documentation and ensure compliance with established procedures.

Required Qualifications

  • 2–3 years of experience in data annotation, QA operations, data operations, or a related field.
  • Experience working with annotation or data-labeling tools.
  • Understanding of QA audits, task tracking, and quality processes.
  • Experience supporting test plans and operational reporting.
  • Strong attention to detail and analytical skills.
  • Good communication and stakeholder coordination skills.
  • Ability to work onsite and manage multiple operational priorities.

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