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Flexible 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 ...

IT Data Analyst

Warner Robins, GA · On-site

$75K - $85K/yr

Position Summary We are seeking a practical, detail-oriented IT Data Analyst to strengthen how our ... Flexible working arrangements, subject to business needs and company policy.

New

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

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

... technologies, and data modeling to help us provide high-performance data solutions ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

... technologies, and data modeling to help us provide high-performance data solutions ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer - GCP

Atlanta, GA · On-site

$110K - $132K/yr

... technologies, and data modeling to help us provide high-performance data solutions ... Flexible work environment and remote work options. Join us and be part of a team building ...

... AI technology and real-time channels that life science companies need to deliver clear, reliable ... Take the time you need with a flexible vacation policy -- recharge your batteries your way Parental ...

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Flexible Data Annotation Tech information

What are some common challenges faced by Flexible Data Annotation Techs, and how can they be addressed?

Flexible Data Annotation Techs often encounter challenges such as maintaining consistency across large volumes of data, adapting to evolving project guidelines, and managing tight deadlines. To address these challenges, it's important to establish clear communication with project leads, regularly review annotation protocols, and utilize available training resources. Building strong attention to detail and staying organized can also help ensure high-quality outputs and job satisfaction.

What is the difference between Flexible Data Annotation Tech vs Data Labeler?

AspectFlexible Data Annotation TechData Labeler
CredentialsBasic computer skills, training in annotation toolsBasic education, sometimes specific software training
Work EnvironmentRemote or on-site, tech-focusedPrimarily remote or on-site, data processing settings
Industry UsageAI, machine learning, data scienceAI, machine learning, data preparation
Job FocusApplying labels to datasets using annotation toolsLabeling data according to guidelines

Flexible Data Annotation Tech roles involve using specialized tools to annotate datasets for AI training, often requiring some technical training. Data Labelers focus on applying labels to data, typically with less technical complexity. Both roles are essential in AI development but differ mainly in technical requirements and scope.

What are the key skills and qualifications needed to thrive as a Flexible Data Annotation Tech, and why are they important?

To thrive as a Flexible Data Annotation Tech, you need attention to detail, accuracy, and a basic understanding of data labeling or annotation processes, often requiring at least a high school diploma. Familiarity with annotation platforms, data labeling tools, and productivity software is typically necessary, and experience with machine learning datasets can be advantageous. Strong time management, communication, and adaptability help you excel in collaborative and ever-changing project environments. These skills ensure high-quality, consistent data output that directly impacts the performance of AI and machine learning systems.

What are Flexible Data Annotation Tech jobs?

Flexible Data Annotation Tech jobs involve labeling, categorizing, or tagging data—such as images, text, audio, or video—to help train machine learning models. These roles are often remote or offer flexible schedules, making them appealing for those seeking adaptable work hours. Tasks can include identifying objects in photos, transcribing audio, or sorting information based on specific guidelines. The work is essential for improving the accuracy of artificial intelligence systems by providing them with high-quality annotated data. No advanced technical skills are usually required, but attention to detail and reliability are important.
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 Flexible Data Annotation Tech jobs in Georgia? For Flexible Data Annotation Tech jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Flexible Data Annotation Tech jobs in Georgia look for? The top searched job categories for Flexible Data Annotation Tech jobs in Georgia are:
What cities in Georgia are hiring for Flexible Data Annotation Tech jobs? Cities in Georgia with the most Flexible Data Annotation Tech job openings:

English (US) Audio QA Annotation Specialist

MatchaTalent

Atlanta, GA • On-site, Remote

Full-time

Posted 16 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