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Internship Ai Data Labeling Jobs in Georgia (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.

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 ...

Tata Consultancy Services

Agentic AI Engineer

Atlanta, GA

$110K - $132K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Tata Consultancy Services

Agentic AI Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Tata Consultancy Services

$110K - $132K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Equifax

Data & Analytics Intern

Alpharetta, GA · On-site

This 12-week Internship Program (May 18-Aug 7, 2026) is a gateway to full-time career paths for ... Enable building the AI/ML prototypes using data, equations, and mathematical results to deliver ...

Tier4 Group

Marketing Internship

Alpharetta, GA · Remote

$14.25 - $19/hr

TAG-CX Marketing & Community Engagement Internship Location: Remote (Atlanta-based preferred for ... data to identify trends and improve performance * Supporting experimentation with AI-powered ...

Revenue Analytics

Data Scientist

Atlanta, GA · On-site +1

$95K - $110K/yr

As a Data Scientist, you will help build machine learning and AI systems that power our hospitality ... field, including internships, research, senior projects, or meaningful independent projects.

Revenue Analytics

Data Scientist

Atlanta, GA · On-site

$95K - $110K/yr

As a Data Scientist, you will help build machine learning and AI systems that power our hospitality ... field, including internships, research, senior projects, or meaningful independent projects.

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Internship Ai Data Labeling information

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

AspectInternship Ai Data LabelingData Annotation Specialist
Required CredentialsHigh school diploma or equivalent; some technical skillsHigh school diploma or higher; technical skills often preferred
Work EnvironmentEntry-level, training-focused, often remote or in-officeProfessional setting, may be remote or on-site, more independent
Employer & Industry UsageTech companies, AI startups, research projectsAI companies, data service providers, tech firms
Search & Comparison IntentUnderstanding entry-level roles in AI data labelingClarifying professional data annotation roles

Internship Ai Data Labeling typically refers to entry-level, training-focused positions aimed at gaining experience in labeling data for AI models. Data Annotation Specialist is a more experienced, professional role involving detailed data labeling tasks. Both roles are essential in AI development, but internships are designed for beginners, while specialists have more responsibility and expertise.

What is an AI data labeling internship?

An AI Data Labeling Internship is a temporary position where interns assist in preparing datasets for machine learning models by accurately annotating, categorizing, or tagging data such as images, text, or audio. Interns learn about the fundamentals of artificial intelligence and the importance of high-quality labeled data in training algorithms. This role is ideal for students or recent graduates interested in AI, data science, or related fields, and provides hands-on experience with data preparation and quality assurance processes.

What are some common challenges faced during an AI data labeling internship, and how can I overcome them?

As an AI Data Labeling intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex labeling guidelines, and managing repetitive tasks without losing focus. To overcome these, it's helpful to regularly review the instructions, seek feedback from your team lead, and use productivity techniques to stay engaged. Collaborating with other interns and attending team meetings can also provide valuable insights and help you address uncertainties quickly.

What are the key skills and qualifications needed to thrive as an AI data labeling intern?

To thrive as an AI Data Labeling Intern, you need attention to detail, basic data analysis skills, and familiarity with data annotation concepts, often supported by a background in computer science or related fields. Experience using annotation platforms, spreadsheets, and sometimes specific labeling software is common, though formal certifications are not usually required. Strong communication, time management, and the ability to follow detailed guidelines set high performers apart in this role. These skills ensure accurate, high-quality data sets that are essential for training reliable AI models.
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Internship Ai Data Labeling jobs near you

AI Data Analyst

RELX Group plc

Alpharetta, GA • On-site

Full-time

Medical, Life

Re-posted 16 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.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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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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