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Data Annotation Tech Jobs in Georgia (NOW HIRING)

AgileEngine

Taxonomy Analyst ID76178

Boston, GA · On-site

... tech platform serving global English-speaking markets. You will standardize job titles, map ... classification, data validation, or data labeling/annotation; - Strong analytical skills ...

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How much do data annotation tech jobs pay per hour?

As of Jul 10, 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.

What are the key skills and qualifications needed to thrive in the Data Annotation Tech position, and why are they important?

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 typical day look like for a Data Annotation Tech?

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.

What is a Data Annotation Tech job?

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.

What are the most commonly searched types of Data Annotation Tech jobs in Georgia? The most popular types of Data Annotation Tech jobs in Georgia are:
What are popular job titles related to Data Annotation Tech jobs in Georgia? For Data Annotation Tech jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Data Annotation Tech jobs in Georgia look for? The top searched job categories for Data Annotation Tech jobs in Georgia are:
What cities in Georgia are hiring for Data Annotation Tech jobs? Cities in Georgia with the most Data Annotation Tech job openings:
Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Georgia as of July 2026, with employment types broken down into 2% Locum Tenens, 30% Full Time, 17% Part Time, 16% Contract, 34% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $40,118 per year, or $19.3 per hour.
Taxonomy Analyst ID76178

Taxonomy Analyst ID76178

AgileEngine

Boston, GA • On-site

Full-time

Posted 4 days ago

Job description


AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Taxonomy Analyst with native-level English fluency to review, annotate, and classify large-scale job and resume datasets according to strict taxonomy guidelines for an HR tech platform serving global English-speaking markets. You will standardize job titles, map occupations, validate metadata, and perform data cleanup across high-volume datasets while adapting content for regional relevance across diverse English markets. The role requires exceptional pattern recognition, attention to detail, and sound independent judgment on ambiguous data points.
WHAT YOU WILL DO
- Review, annotate, and classify large-scale datasets (job descriptions, resumes, and skill profiles) according to strict taxonomy guidelines;
- Support daily operations by standardizing job titles, mapping occupations, validating metadata, and continuously improving overall taxonomy quality;
- Perform data cleanup and validation to identify patterns, resolve inconsistencies, and ensure accurate, standardized outputs;
- Adapt and validate multilingual and localized content to ensure regional relevance across diverse English markets;
- Strictly follow established labeling guidelines while exercising sound, independent judgment on ambiguous data points.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- Native-level fluency in English;
- 3+ years of proven experience in taxonomy, metadata management, content classification, data validation, or data labeling/annotation;
- Strong analytical skills, exceptional attention to detail, and sharp pattern recognition abilities;
- Proven experience reviewing, processing, and navigating high-volume datasets.
NICE TO HAVES
- Market knowledge or familiarity with the professional landscapes of Ireland, India, the United Arab Emirates, Australia, or Singapore;
- Domain knowledge in HR tech, recruitment, or job taxonomy (occupational mapping, labor market structures);
- Proficiency with Excel / Google Sheets or basic SQL queries;
- Hands-on experience working with LLMs / AI tools (e.g., ChatGPT, Gemini, Claude) for data curation or evaluation.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.

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