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Full Time Data Annotation Tech Jobs (NOW HIRING)

This is a full-time position (W2 or 1099 is fine). You would be employed by Cyborg Mobile but ... Design judgment guidelines and instructions for data annotation, validation, and quality control

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Full Time Data Annotation Tech information

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How much do full time data annotation tech jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for full time data annotation tech in the United States is $22.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What is a full time data annotation tech?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a full time data annotation tech?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

How does a full time data annotation tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What is the difference between Full Time Data Annotation Tech vs Data Labeling Specialist?

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Does full time data annotation tech actually pay?

Full-time data annotation technicians typically receive a regular salary or hourly wage, with pay rates varying based on experience, location, and company. Many roles offer benefits such as paid time off and health insurance, and some positions may require familiarity with annotation tools or specific data types.
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Infographic showing various Full Time Data Annotation Tech job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.

Data Annotation Quality Control Analyst

Saint Louis, MO • On-site

Enabled Intelligence
11 - 50 employees

$23/hr

Full-time

Re-posted 20 days ago


Job description

Data Annotation Quality Control Analyst About Enabled Intelligence, Inc. Enabled Intelligence, Inc. provides extremely accurate, precise and secure data labeling and AI solutions to help our government and commercial customers effectively deploy reliable and unbiased artificial intelligence technologies. We leverage the unique talents of veterans, people with different abilities, and subject matter experts to unlock the value of data to improve the delivery of public services and mission critical national security programs.  Every Enabled solution starts with a team of highly-trained, US based data analysts that have both subject-matter expertise as well as a deep understanding of the best techniques and tools for AI data annotation, model development, and testing and evaluation.    At EI we respect and celebrate individuals from all walks of life. Our different backgrounds, cultures, experiences, and way of thinking make us stronger together and result in the most accurate and reliable AI solutions for our clients. We are extremely committed to a culture and environment where excellence can be achieved!  If the idea of working in a collaborative, energetic and people focused environment where we are working together to build something meaningful excites you, Enabled Intelligence might just be the team you are looking for!  Data Annotation Quality Control Analyst Data annotation is an essential component in training artificial intelligence/machine learning (AI/ML) algorithms. Accuracy of the data used to train AI models is one of the biggest factors in the effectiveness of the AI performance. As a member of the Enabled Intelligence Quality Control team, your role is to help ensure our clients receive the highest quality of data. You will review data such as geospatial imagery (EO, RGB, IR, SAR), Full Motion Video, and types of documents that have been annotated to identify and correct errors such as missed objects, miss-classifications and false positives. You will be responsible for recognizing patterns and sharing this analysis with project managers and the director of Quality Delivery. Joining our team means playing an integral role for the future of government AI/ML capabilities. Responsibilities Use advanced analytic tools to review data (EO, RGB, IR, SAR, FMV) that has been annotated to identify and correct errors such as missed objects, miss-classifications and false positivesDiligently track and analyze patterns of errors and keep Project Managers and the Director of Quality Delivery up to dateProcess project data according to established procedures and guidelines Provide feedback and ideas on process improvements or concerns that may impact project performance Required Qualifications and Skills Strong computer skills including proficiency in Excel and PowerPoint Strong analytical skills, visual spatial recognition, pattern recognition and attention to detail Ability to follow directions and meet deadlines Ability to communicate reliably Ability to be a team player and work with individuals with different communication, learning and working stylesAbility to work independently including managing your schedule, attending all required meetings and completing projects within a deadline Ability to work out of the Enabled Intelligence office located in St. Louis, MO Monday-Friday during normal business hours Must be a US Citizen Desired Qualifications and SkillsPrevious imagery-based Data Annotation or feature extraction experience including EO, RGB, IR, SAR and/or FMVPrevious Data Annotation Quality Control experience Ability to answer project questions and provide one on one performance feedback to Data Annotators Prior experience with business productivity tools like Microsoft Office, and/or Slack Highschool Degree Physical Requirements Prolonged periods of sitting at a desk and working on a computer Background Check & Security Clearance Applicants selected will be subject to background investigation and must meet requirements for employment.
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