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Remote Data Annotation Specialist Jobs in Utah (NOW HIRING)

Sorenson

Senior Sign Language Specialist

Salt Lake City, UT · On-site +1

$66K/yr

Maintain accurate records of annotation work, decisions, and edge cases in team tooling and ... Able to sit/stand for long periods of time in an office or remote work environment. * Dexterity of ...

Maxwell Power

Data Entry Specialist

Salt Lake City, UT · Remote

$20/hr

Data Entry Specialist About Maxwell Power At Maxwell Power, we are transforming how renewable ... Communicate with remote solar technicians and utility partners to clarify data requirements and ...

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HumanSignal

$55K - $100K/yr

... data collection and annotation -- delivering the datasets that frontier AI research requires and remote workforce marketplaces can\'t. We own projects end-to-end, from scoping and protocol design ...

RainFocus

Integration Specialist (Remote)

Lehi, UT · On-site +1

The integrations may include data transfers with third party vendors such as Zoom and other media ... Integrations Specialists will also support Single Sign On through client's web sites. Primary ...

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Remote Data Annotation Specialist information

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

To thrive as a Remote Data Annotation Specialist, you need strong attention to detail, familiarity with data labeling guidelines, and a basic understanding of data structures, often supported by a high school diploma or relevant training. Experience with annotation platforms, data management tools, and sometimes basic scripting languages is typically required. Excellent time management, communication skills, and the ability to work independently help individuals excel in this remote role. These skills ensure high-quality, consistent, and efficient data labeling, which is critical for training accurate machine learning models.

What is the salary of data annotation specialist?

The salary of a remote data annotation specialist typically ranges from $12 to $25 per hour, depending on experience, skill level, and the complexity of annotation tasks. Some positions may offer hourly wages or project-based pay, with opportunities for bonuses or raises based on performance and accuracy.

What are some typical challenges Remote Data Annotation Specialists face, and how can they be managed?

Remote Data Annotation Specialists often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistency across large datasets, and managing tight deadlines. To overcome these, it's helpful to establish a structured work schedule, take regular breaks, and utilize annotation guidelines provided by the employer. Collaborative tools and periodic check-ins with team leads or peers can also help clarify questions and maintain quality standards, ensuring annotation accuracy and productivity.

What is a data annotation specialist?

A data annotation specialist is a professional who labels and categorizes data, such as images, text, or videos, to help train machine learning models. They typically use annotation tools and require attention to detail to ensure data accuracy, often working remotely with flexible schedules.

How much do remote data annotation operators make?

Remote data annotation specialists typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some roles may offer project-based pay or bonuses for accuracy and efficiency, with opportunities for skill development in annotation tools and data labeling processes.

What are Remote Data Annotation Specialists?

Remote Data Annotation Specialists are professionals who label, tag, or categorize data—such as images, text, audio, or video—for use in machine learning and artificial intelligence projects. They work remotely, using specialized software tools to ensure data is accurately annotated according to project guidelines. Their work helps improve the performance of AI systems by providing high-quality, labeled datasets that algorithms can learn from. This role often requires attention to detail, basic technical skills, and the ability to follow instructions carefully.

What qualifications do you need to be a data annotator?

To be a remote data annotation specialist, candidates typically need strong attention to detail, basic computer skills, and familiarity with annotation tools or software. A high school diploma or equivalent is usually sufficient, and some roles may require prior experience in data labeling or related tasks. Good communication skills and the ability to work independently are also beneficial.

What is the difference between Remote Data Annotation Specialist vs Remote Data Labeler?

AspectRemote Data Annotation SpecialistRemote Data Labeler
CredentialsHigh school diploma or equivalent; attention to detailHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote, often part of AI/ML teamsRemote, typically freelance or contract-based
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, computer vision
Common Search IntentUnderstanding roles, job requirements, and career pathFinding entry-level or freelance annotation jobs

The Remote Data Annotation Specialist and Remote Data Labeler roles both involve labeling data for AI and machine learning projects. However, the Specialist often performs more complex annotations and may work within a team, while the Labeler typically handles simpler tasks independently. Both roles require attention to detail and are common in AI industries, but the Specialist may have more responsibilities and slightly higher skill expectations.

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Remote Data Annotation Specialist jobs near you

English (US) Audio QA Annotation Specialist

MatchaTalent

Salt Lake City, UT • On-site, Remote

Full-time

Posted 17 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