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Freelance Ai Data Labeling Jobs in Decatur, GA (NOW HIRING)

RELX Group plc

AI Data Analyst

Alpharetta, GA · On-site

Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning ... Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.

RELX

AI Data Analyst

Alpharetta, GA

Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning ... Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.

LexisNexis

AI Data Analyst

Alpharetta, GA · On-site

Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning ... Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.

Accenture

Data Protection Consultant

Atlanta, GA

$112K - $133K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced ... Build awareness and controls for emerging AI and agentic AI security considerations (e.g., Security ...

micro1 AI

First-Person AI Video Trainer

Atlanta, GA · Remote

$13/hr

No prior experience in AI is required -- your domain knowledge is what matters. Key ... data. * Follow detailed technical protocols to ensure all submissions meet strict quality, labeling ...

Insight Global

AI Engineer

Atlanta, GA · On-site +1

... tenant data leakage occurs. • Contribute to model behaviour evaluation -- running prompt ... dataset and labeling workflow. • Familiarity with prompt-injection risks and mitigation ...

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All JobsAi Data Labeling JobsFreelance Ai Data Labeling JobsFreelance Ai Data Labeling Jobs in Decatur, GA

Freelance Ai Data Labeling information

See Decatur, GA salary details

$14

$46

$129

How much do freelance ai data labeling jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for freelance ai data labeling in Decatur, GA is $46.58, according to ZipRecruiter salary data. Most workers in this role earn between $23.70 and $60.34 per hour, depending on experience, location, and employer.

What is freelance AI data labeling?

Freelance AI data labeling involves working independently to annotate or tag data, such as images, text, audio, or video, to help train artificial intelligence and machine learning models. Freelancers are hired by companies or platforms to manually identify and categorize data so that algorithms can learn to recognize patterns and make accurate predictions. This work is essential for improving the accuracy and performance of AI systems in various applications, including self-driving cars, voice assistants, and content moderation. Typically, freelancers need attention to detail, basic technical skills, and sometimes domain-specific knowledge, depending on the project's requirements.

What is the difference between Freelance Ai Data Labeling vs Data Annotation Specialist?

AspectFreelance Ai Data LabelingData Annotation Specialist
CredentialsNone required, but familiarity with labeling tools helpsOften requires training or certification in annotation tools
Work EnvironmentRemote, flexible freelance projectsTypically employed by companies or agencies, sometimes remote
Employer & IndustryFreelance platforms, AI/ML industryTech companies, AI development teams
Search & Comparison IntentLooking for freelance labeling jobsSeeking full-time or contract annotation roles

Freelance Ai Data Labeling involves independently completing labeling tasks for various clients, offering flexibility and project-based work. Data Annotation Specialists often work within organizations or agencies, focusing on detailed annotation tasks as part of a team. Both roles require knowledge of labeling tools, but freelancers typically have more varied projects, while specialists may have more structured employment settings.

What are the key skills and qualifications needed to thrive as a Freelance AI Data Labeler, and why are they important?

To thrive as a Freelance AI Data Labeler, you need strong attention to detail, basic understanding of machine learning concepts, and the ability to follow complex guidelines accurately, usually supported by a high school diploma or higher education. Familiarity with data annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes specific domain knowledge is often required. Excellent time management, reliability, and clear communication help freelancers stand out in delivering high-quality, consistent results. These skills ensure that labeled data is accurate and reliable, directly impacting the effectiveness of AI models and client satisfaction.

What are some typical challenges faced by freelance AI data labelers, and how can they be managed?

Freelance AI data labelers often encounter challenges such as maintaining accuracy while working with large volumes of repetitive data, understanding complex labeling guidelines, and managing tight deadlines across multiple clients. Effective strategies include regularly reviewing project instructions, using productivity tools to track progress, and seeking clarification from clients when uncertainties arise. Maintaining open communication with project managers and participating in feedback sessions can also help improve labeling quality and efficiency.
What are popular job titles related to Freelance Ai Data Labeling jobs in Decatur, GA? For Freelance Ai Data Labeling jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Freelance Ai Data Labeling jobs in Decatur, GA look for? The top searched job categories for Freelance Ai Data Labeling jobs in Decatur, GA are:
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Freelance Ai Data Labeling jobs near you
AI Data Analyst

AI Data Analyst

RELX Group plc

Alpharetta, GA • On-site

Full-time

Medical, Life

Posted 27 days ago

Job description

Are you passionate about improving data quality and readiness to unlock the full potential of AI solutions?
Do you enjoy collaborating across teams to ensure data is structured, governed, and usable for intelligent systems?
About the Business:
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,
https://risk.lexisnexis.com
About the Team:
We are a newly formed Enterprise AI team focused on enabling agent-based solutions across the organization. We build and manage the environments, platforms, and guardrails that allow teams to create, test, and scale AI agents safely and efficiently turning experimentation into real business impact.
We're a team of curious builders and operators who are constantly exploring, learning, and applying new AI tools and approaches to solve real-world problems and improve how work gets done.
About the Role:
We are seeking an AI Data Analyst to support teams in preparing and maintaining AI-ready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality, metadata, and governance, helping teams understand how to structure, document, and manage their data so it can be safely and effectively used by AI systems.
The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own end-to-end data pipelines and is not expected to be a deep technical expert in RAG or embeddings, but should have a solid working understanding of AI-driven data needs.
Responsibilities:
AI Data Readiness Support
  • Work with product and delivery teams to assess whether datasets and content are fit for AI use cases.
  • Help teams understand and apply AI data readiness standards, including quality, freshness, metadata, and access expectations.
  • Identify common data issues that impact AI outcomes (e.g., stale data, unclear ownership, missing metadata) and recommend remediation steps.
  • Contribute to repeatable checklists, guidance, or documentation that help teams prepare data for AI.

Data Quality & Relevance
  • Support data quality checks focused on accuracy, completeness, consistency, and timeliness for AI-consumed data.
  • Assist in monitoring and validating data freshness and relevance, escalating issues to engineering or data owners as needed.
  • Help teams improve data clarity and usability to reduce ambiguity in AI outputs.

Metadata & Semantic Enablement
  • Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content.
  • Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning (in coordination with engineering teams).
  • Promote good content hygiene practices (clear structure, consistent naming, well-scoped documents).

AI Data Sources & Retrieval (Support Role)
  • Support the upkeep and documentation of approved data sources used by AI solutions.
  • Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.
  • Collaborate with AI and platform teams on data inclusion/exclusion decisions without owning technical implementation.

Governance, Lineage & Compliance Awareness
  • Help teams align AI-consumed data with enterprise governance requirements, including classification, access controls, and retention.
  • Support basic data lineage and ownership documentation for AI-relevant datasets.
  • Partner with governance and security teams by surfacing risks or gaps; does not act as final approval authority.

What This Role Does Not Own
  • Does not design or own end-to-end production data pipelines.
  • Does not act as the primary technical owner for RAG frameworks, vector databases, or embedding strategies.
  • Does not make final governance or compliance decisions independently.

Requirements:
  • Proven experience in data analysis, analytics engineering, data operations, or data quality roles.
  • Good understanding of data quality principles and how poor data impacts downstream systems.
  • Experience working with structured and unstructured data (tables, files, documents, knowledge assets).
  • Proficiency in SQL and comfort investigating data issues.
  • Familiarity with data governance fundamentals (classification, access controls, ownership, retention).
  • Strong communication skills and ability to explain data concepts to non-technical stakeholders.

Preferred Qualifications
  • Exposure to AI-enabled products, copilots, or search-based solutions.
  • Basic familiarity with AI data concepts such as semantic search, embeddings, or retrieval patterns.
  • Experience working in enterprise or regulated environments.
  • Experience contributing to standards, playbooks, or shared data practices.

What Success Looks Like
  • Teams can reliably prepare datasets that meet AI readiness expectations with less rework.
  • AI solutions benefit from more relevant, up-to-date, and understandable data.
  • Clear ownership and documentation exist for data used by AI systems.
  • Strong collaboration between delivery teams, data engineering, and governance.

Working for You:
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
  • Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
  • Life Assurance Policies: Providing financial security for your loved ones.
  • Modern Family Benefits: Support for maternity, paternity, and adoption needs.
  • Long Service Award: Recognition for your dedication and loyalty.
  • Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
  • Flexible Benefits Plan : Offering you wider choice of services and products
  • Employee Assistance Program : Access support for personal and work-related challenges.
  • Flexible Working Arrangements: Balance work and personal life effectively.
  • Access to Learning and Development Resources: Empowering your professional growth.

Risk benefit statement
Learn more about the LexisNexis Risk team and how we work: https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000
U.S. National Base Pay Range: $78,800 - $131,300. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Ohio, the base pay range is $74,900 - $124,700.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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