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Assistant Ai Labeling Jobs in Georgia (NOW HIRING)

RELX Group plc

AI Data Analyst

Alpharetta, GA · On-site

Metadata & Semantic Enablement * Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content. * Support basic semantic labeling or ...

LexisNexis

AI Data Analyst

Alpharetta, GA · On-site

Metadata & Semantic Enablement * Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content. * Support basic semantic labeling or ...

RELX

AI Data Analyst

Alpharetta, GA

Metadata & Semantic Enablement * Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content. * Support basic semantic labeling or ...

Flex HR

Material Handler

Sandersville, GA · On-site

$14 - $17/hr

You'll also play a key role in packaging and labeling finished goods -- making sure the right ... production; assist in raw material make down • Support mechanical repairs and preventative ...

Flex HR

Material Handler

Sandersville, GA

$14 - $17/hr

You'll also play a key role in packaging and labeling finished goods -- making sure the right ... production; assist in raw material make down • Support mechanical repairs and preventative ...

Flex HR

Material Handler

Alpharetta, GA

$16.25 - $19.75/hr

You'll also play a key role in packaging and labeling finished goods -- making sure the right ... production; assist in raw material make down • Support mechanical repairs and preventative ...

Cennox

Material Handler

Alpharetta, GA · On-site

$16.25 - $19.75/hr

... assist with audits. • Label and organize materials for efficient workflow. • Follow FIFO or ... Notice on Use of AI in Hiring As part of our commitment to fair and efficient hiring practices ...

Cennox

Material Handler

Alpharetta, GA · On-site

$16.25 - $19.75/hr

... assist with audits. • Label and organize materials for efficient workflow. • Follow FIFO or ... Notice on Use of AI in Hiring As part of our commitment to fair and efficient hiring practices ...

Cennox

Material Handler

Alpharetta, GA · On-site

$16.25 - $19.75/hr

... assist with audits. • Label and organize materials for efficient workflow. • Follow FIFO or ... Notice on Use of AI in Hiring As part of our commitment to fair and efficient hiring practices ...

The Archetype Strategy

Lead Technician

Atlanta, GA · On-site

$42K - $54K/yr

... terminations, labeling, testing, and clean-up * Ensure all work is performed according to site ... Maintain a clean, organized, and safe work environment * Assist with conflict resolution and ...

Deloitte

Cyber Data Protection Manager

Atlanta, GA · Remote

$106K - $144K/yr

DLP, sensitivity labels, data classification, DSPM, DSPM for AI, on-demand classification, or ... Perform the role of mentor and coach to assist junior staff to develop skills by providing feedback ...

Dick's Sporting Goods

Teammate Footwear

Alpharetta, GA

$16.50 - $22.25/hr

As a Teammate - Footwear , you will assist with product selection, merchandise expertise, and ... AI tools are not permitted to be used by the candidate during any part of the interview process.

Dick's Sporting Goods

Teammate Footwear

Alpharetta, GA · On-site

$16.50 - $22.25/hr

As a Teammate - Footwear , you will assist with product selection, merchandise expertise, and ... AI tools are not permitted to be used by the candidateduring any part of the interview process.

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All JobsAssistant Ai Labeling JobsAssistant Ai Labeling Jobs in Georgia

Assistant Ai Labeling information

What's the easiest AI job to get?

Entry-level AI-related jobs like data labeling or annotation are generally the easiest to obtain, as they require minimal technical skills and often offer flexible schedules. These roles involve reviewing and tagging data to help train AI models and typically do not require advanced degrees or certifications.

What is the difference between Assistant Ai Labeling vs Data Annotator?

AspectAssistant Ai LabelingData Annotator
CredentialsHigh school diploma or equivalent; some roles may require basic technical skillsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentRemote or office-based; collaborative with AI teamsPrimarily remote; focused on data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics
Search & Comparison IntentUnderstanding roles supporting AI trainingData labeling and annotation tasks for AI models

Assistant Ai Labeling involves supporting AI systems by labeling data, often requiring some technical understanding. Data Annotator focuses on labeling data to prepare datasets for AI training. Both roles are essential in AI development, with overlapping skills but different focus areas.

What is an AI labeling job?

An AI labeling job involves reviewing and annotating data such as images, videos, or text to help train machine learning models. Workers typically use specialized tools to add tags or labels that enable AI systems to recognize patterns and make decisions. These jobs often require attention to detail and may be performed remotely with flexible schedules.

How to become a data labeler?

To become a data labeler, you typically need basic computer skills, attention to detail, and the ability to follow instructions. Many positions require no formal education, but familiarity with data annotation tools and understanding of the specific data type (images, text, audio) can be helpful. Some companies may require completing a training or assessment before starting the job.

What are Assistant AI Labeling jobs?

Assistant AI Labeling jobs involve reviewing, tagging, and categorizing data such as images, text, or audio to help train artificial intelligence and machine learning models. These roles are essential because accurate labeling ensures that AI systems can learn to recognize patterns and make decisions effectively. Tasks may include drawing bounding boxes around objects in images, transcribing spoken words, or classifying text according to given guidelines. The work is often done using specialized software and requires attention to detail as well as consistency. Assistant AI Labelers may work remotely or in-house for tech companies, research organizations, or data annotation firms.

What are some common challenges faced by Assistant AI Labeling professionals, and how can they be addressed?

Assistant AI Labeling professionals often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially with ambiguous or subjective cases. To address these challenges, most teams implement clear annotation guidelines, regular training sessions, and peer review processes to ensure high-quality outputs. Collaboration with data scientists and project managers is also key, as open communication helps clarify uncertainties and align labeling practices with project goals. Embracing feedback and staying flexible as guidelines evolve can further enhance both the quality of work and job satisfaction in this role.

What are the key skills and qualifications needed to thrive as an Assistant AI Labeling Specialist, and why are they important?

To thrive as an Assistant AI Labeling Specialist, you need strong attention to detail, accuracy, and an understanding of data annotation practices, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools, and sometimes basic knowledge of programming languages like Python is beneficial. Dependability, time management, and the ability to follow complex instructions are crucial soft skills for excelling in this role. These skills ensure high-quality labeled data, which is vital for training accurate and reliable AI models.

How much do data labelers typically earn?

Data labelers, including assistant AI labelers, typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Some positions may offer project-based pay or bonuses for accuracy and efficiency.
What are the most commonly searched types of Ai Labeling jobs in Georgia? The most popular types of Ai Labeling jobs in Georgia are:
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What job categories do people searching Assistant Ai Labeling jobs in Georgia look for? The top searched job categories for Assistant Ai Labeling jobs in Georgia are:
What cities in Georgia are hiring for Assistant Ai Labeling jobs? Cities in Georgia with the most Assistant Ai Labeling job openings:
Assistant Ai Labeling jobs near you
AI Data Analyst

AI Data Analyst

RELX Group plc

Alpharetta, GA • On-site

Full-time

Medical, Life

Posted 10 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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