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Data Annotation Ai Trainer Jobs in Arizona (NOW HIRING)

Senior Data Engineer / Data Curator

Phoenix, AZ ยท On-site

$130K - $177K/yr

... AI models is high-quality, well-organized, and fit for use in model training and deployment. You ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

Senior Data Engineer / Data Curator

Phoenix, AZ ยท On-site

$130K - $177K/yr

... AI models is high-quality, well-organized, and fit for use in model training and deployment. You ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Vertex AI (e.g., Model Garden, Agent Builder, custom training); Gemini API and Google AI Studio; BigQuery (for data processing and analytics); Cloud Run, Cloud Functions, and GKE (for agent ...

Design, implement, and facilitate high-impact AI/ML, data science, and generative AI training programs, workshops, and self-paced learning modules tailored for various university audiences (faculty ...

This position will lead the development, oversight, and management of AI/ML and data science training initiatives across the University of Arizona. The incumbent will work onsite at the University of ...

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Data Annotation Ai Trainer information

Is data annotation AI trainer legit?

Data annotation AI trainer roles involve labeling data to help train machine learning models and are generally legitimate jobs in the AI industry. These positions often require attention to detail and familiarity with annotation tools, and they can be found with reputable companies or platforms. However, job seekers should verify the employer's credibility and be cautious of scams or unrealistic promises.

Does data annotation really pay?

Data annotation jobs, including roles like AI trainer, typically pay hourly or per task rates that can range from minimum wage to higher amounts depending on experience and complexity. Many companies offer remote work with flexible schedules, and pay can vary based on skill level, project requirements, and the platform used for job postings.

How much do AI data trainers make?

AI data trainers typically earn between $15 and $30 per hour, depending on experience, location, and the complexity of tasks. Many roles are freelance or part-time, requiring skills in data labeling, annotation tools, and understanding of AI models.

How much do data annotation AI trainers make?

Data annotation AI trainers typically earn between $15 and $30 per hour, depending on experience, location, and the complexity of the annotation tasks. Entry-level positions may pay closer to the lower end, while experienced trainers with specialized skills can earn higher wages, often working remotely with flexible schedules.

What is a Data Annotation AI Trainer job?

A Data Annotation AI Trainer is responsible for labeling and annotating data to help train machine learning models. This involves identifying objects, tagging text, or categorizing images to improve AI accuracy. The role requires attention to detail and an understanding of guidelines to ensure high-quality labeled data. AI trainers work closely with data scientists and engineers to refine model performance through precise annotations.

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

To thrive as a Data Annotation Ai Trainer, you need a keen attention to detail, basic data analysis skills, and familiarity with machine learning concepts, often supported by a relevant degree or coursework. Experience with annotation tools like Labelbox, Supervisely, or similar platforms, along with knowledge of data privacy standards, is commonly required. Strong communication, problem-solving ability, and patience help you work effectively in teams and ensure data quality. These skills are essential because they directly influence the accuracy and effectiveness of AI models trained using annotated data.

What does a typical day look like for a Data Annotation Ai Trainer?

As a Data Annotation Ai Trainer, your typical day involves reviewing and labeling large datasets, providing feedback to annotation teams, and ensuring that data quality meets project standards. You'll often collaborate with data scientists, machine learning engineers, and project managers to clarify guidelines and resolve ambiguities. Periodically, you may help develop or refine documentation and training materials to improve annotation consistency. The role requires both independent work and open communication to maintain high accuracy and support AI development initiatives.

What are popular job titles related to Data Annotation Ai Trainer jobs in Arizona? For Data Annotation Ai Trainer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Data Annotation Ai Trainer jobs in Arizona look for? The top searched job categories for Data Annotation Ai Trainer jobs in Arizona are:
What cities in Arizona are hiring for Data Annotation Ai Trainer jobs? Cities in Arizona with the most Data Annotation Ai Trainer job openings:
Infographic showing various Data Annotation Ai Trainer job openings in Arizona as of July 2026, with employment types broken down into 33% Full Time, and 67% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.

English (US) Audio QA Annotation Specialist

MatchaTalent

Phoenix, AZ โ€ข 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