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Data Annotation Tech Jobs in Georgia (NOW HIRING)

Data annotation and quality review * Exploratory data analysis and model fail state analysis ... We use the latest in AI/ML technology to help our customers break new ground at scale. We are a ...

Data annotation and quality review * Exploratory data analysis and model fail state analysis ... We use the latest in AI/ML technology to help our customers break new ground at scale. We are a ...

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

... annotation, and symbology * Engage in storm restoration activities * Validate GIS model connectivity and correct connectivity issues * /Perform quality control and data validation activities

Data Annotation Tech information

See Georgia salary details

$10

$19

$29

How much do data annotation tech jobs pay per hour?

As of Aug 4, 2026, the average hourly pay for data annotation tech in Georgia is $19.29, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $22.93 per hour, depending on experience, location, and employer.

How to become a data annotation tech?

To become a data annotation tech, you typically need a high school diploma or equivalent, strong attention to detail, and familiarity with data labeling tools or software. Some roles may require basic knowledge of machine learning concepts or specific platforms like Labelbox or CVAT. Gaining experience through online courses or tutorials can also improve job prospects.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

Does data annotation actually pay you?

Data annotation jobs typically pay hourly or per task, with rates varying depending on the platform and complexity of the work. Many companies and platforms offer remote opportunities that provide consistent payment once tasks are completed, often requiring basic skills in data labeling tools. Payment is generally reliable for those who meet quality standards and adhere to deadlines.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

How much do data annotation technicians make?

Data annotation technicians typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Many roles are entry-level and may offer flexible schedules or remote work opportunities.
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Infographic showing various Data Annotation Tech job openings in Georgia as of July 2026, with employment types broken down into 2% Locum Tenens, 35% Full Time, 26% Part Time, 1% Temporary, 1% Contract, and 35% Nights. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution, with an average salary of $40,118 per year, or $19.3 per hour.

English (US) Audio QA Annotation Specialist

MatchaTalent

Atlanta, GA • On-site, Remote

Full-time

Posted 20 days ago


Job description

This role requires the candidate to work remotely from the United States.


Client Overview

Our client is a global artificial intelligence technology company specializing in the development of advanced large language models (LLMs), speech recognition technologies, multilingual AI systems, and data annotation solutions. The organization collaborates with leading AI research laboratories and enterprise technology companies worldwide to accelerate the development of next-generation artificial intelligence through high-quality human-generated data.

Supporting a diverse portfolio of multilingual AI initiatives, the company works with language specialists, voice professionals, and annotation experts across the globe to improve the accuracy, contextual understanding, and performance of cutting-edge AI systems used in speech processing, conversational AI, and natural language understanding.


Job Role

The English (US) Audio QA Annotation Specialist is responsible for reviewing, evaluating, and validating English (US) audio recordings to ensure they meet the highest quality standards required for AI speech recognition and audio annotation projects.

Working as part of a multilingual quality assurance team, this role focuses on assessing recording accuracy, pronunciation, fluency, audio clarity, annotation consistency, and compliance with project guidelines. The successful candidate will help ensure that all approved audio data contributes effectively to the development of advanced multilingual AI speech technologies.


Key Responsibilities

  • Review and evaluate English (US) audio recordings for quality, pronunciation accuracy, clarity, and natural speech delivery.
  • Verify annotation accuracy and ensure all submitted recordings comply with project guidelines and quality standards.
  • Identify audio quality issues including background noise, recording inconsistencies, pronunciation errors, or technical defects.
  • Provide structured quality feedback and recommend improvements when recordings do not meet required standards.
  • Ensure consistency across annotated datasets by following established QA processes and evaluation criteria.
  • Collaborate with project reviewers and annotation teams to maintain high-quality multilingual datasets.
  • Maintain accurate documentation of review outcomes and quality assurance findings.
  • Support the continuous improvement of AI speech recognition models through high-quality audio validation.


Candidate Requirements

  • Native-level fluency in English (US) with excellent listening comprehension and pronunciation knowledge.
  • Minimum 1 year of experience in audio quality assurance, audio annotation, localization, transcription review, voice-over, dubbing, ADR, or related language quality roles.
  • Strong attention to detail with the ability to identify pronunciation, fluency, and audio quality issues accurately.
  • Excellent understanding of American English linguistic nuances, regional accents, grammar, and natural speech patterns.
  • Experience reviewing audio recordings and applying quality standards consistently.
  • Familiarity with audio editing or audio playback software is preferred.
  • Strong analytical skills with the ability to provide clear and actionable quality feedback.
  • Ability to work independently while meeting project deadlines and quality targets.


Job Code: #784