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Data Annotation Research Jobs in Beverly, MA (NOW HIRING)

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

Vrtx

Pathology Research Scientist

Boston, MA

$105K - $158K/yr

Pathobiology Research Scientist will perform routine and specialized histology techniques, wet lab ... Knowledge and experience with image review, annotation, and visual data analysis using image ...

Motional

Staff Front End Engineer

Boston, MA · On-site +1

$172K - $229K/yr

Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to ... Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a ...

Motional

Staff Front End Engineer

Boston, MA · On-site +1

$172K - $229K/yr

Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to ... Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a ...

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All JobsData Annotation Research JobsData Annotation Research Jobs in Beverly, MA

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

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

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
What cities near Beverly, MA are hiring for Data Annotation Research jobs? Cities near Beverly, MA with the most Data Annotation Research job openings:
Data Annotation Research jobs near you

English (US) Audio QA Annotation Specialist

MatchaTalent

Boston, MA • On-site, Remote

Full-time

Posted 14 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