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Full Time Data Annotation Specialist Jobs (NOW HIRING)

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Welocalize, Inc.

OR · On-site

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Welocalize, Inc.

OR · On-site

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

... annotation activities, and ensures data readiness, traceability, and compliance throughout the AI ... Please note - this is a full time, onsite role located in Waukesha, WI. Roles and Responsibilities ...

Level Data LLC

Data Solutions Specialist

Boston, MA · Remote

$65K - $70K/yr

Full-time | Data & Analytics **About the role** Data is at the heart of everything we do. As a Data Solutions Specialist, you'll be the person who takes messy, real-world education data and makes it ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

Own Figure's external annotation and review vendor strategy end to end, from sourcing through ... The US base salary range for this full-time position is between $120,000 - $180,000 annually. The ...

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Full Time Data Annotation Specialist information

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$28K

$72.9K

$88K

How much do full time data annotation specialist jobs pay per year?

As of Jun 15, 2026, the average yearly pay for full time data annotation specialist in the United States is $72,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $87,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Full Time Data Annotation Specialists, and how can they be managed?

Full Time Data Annotation Specialists often encounter challenges such as maintaining high accuracy while working with large volumes of data, staying focused during repetitive tasks, and adapting to evolving annotation guidelines. Managing these challenges involves developing an eye for detail, regularly reviewing updated instructions, and using productivity techniques like taking short breaks or collaborating with team members to discuss ambiguities. Additionally, many organizations provide ongoing training and support to ensure consistency and quality in annotations.

What is the difference between Full Time Data Annotation Specialist vs Data Labeling Technician?

AspectFull Time Data Annotation SpecialistData Labeling Technician
CredentialsHigh school diploma or equivalent; some roles prefer certifications in data annotationHigh school diploma or equivalent; minimal certifications required
Work EnvironmentOffice or remote; collaborative with data science teamsWarehouse or office; focused on labeling tasks
Industry UsageUsed across AI, machine learning, and data science industriesPrimarily in AI and machine learning sectors for data preparation

The Full Time Data Annotation Specialist and Data Labeling Technician roles both involve preparing data for AI models. The specialist typically has broader responsibilities, may require certifications, and works in collaborative environments, while the technician focuses on specific labeling tasks with minimal credentials. Both roles are essential in the data annotation process within AI industries.

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

To thrive as a Full Time Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or higher. Proficiency in using annotation tools (such as Labelbox or Supervisely), spreadsheets, and sometimes basic scripting is typically required. Excellent communication, time management, and the ability to follow detailed instructions help you stand out in this role. These skills and qualities are crucial to ensure high-quality, accurate datasets that drive effective machine learning and AI model development.

What is a Full Time Data Annotation Specialist?

A Full Time Data Annotation Specialist is a professional responsible for labeling and categorizing data, such as images, text, audio, or video, to help train machine learning models. Their primary role involves accurately tagging or marking data according to specific guidelines, which is essential for artificial intelligence and machine learning applications. This job often requires attention to detail, consistency, and sometimes domain-specific knowledge, depending on the project. Data annotation specialists typically work in industries like technology, healthcare, autonomous vehicles, and e-commerce. Full-time positions usually offer stable hours and may include benefits.
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Full Time Data Annotation Specialist jobs near you
Infographic showing various Full Time Data Annotation Specialist job openings in the United States as of June 2026, with employment types broken down into 65% Full Time, and 35% Part Time. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $72,947 per year, or $35.1 per hour.
Data Labeling Associate

Data Labeling Associate

Welocalize, Inc.

New York, NY

$17.50 - $22.75/hr

Full-time

Posted 17 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

336th of 428 rated business services

Job description

If you have a Candidate Login already, but have forgotten your password please use the steps to reset your password. If you have forgotten your email login, please contact servicedesk@welocalize.com subject Workday Candidate Login

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Job Responsibilities:

The ideal candidate will have a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. They will play a pivotal role in updating our machine learning models and ensuring their efficacy.

MAIN TASKS & RESPONSIBILITIES

Machine Learning Model Updates:

  • Update training and test model databases with new or amended synthetic textual and image data.
  • Modify and refine machine learning data creation, annotation, and rating guidelines.

Model Training and Evaluation:

  • Initiate model training processes using internal tools and command-line interfaces.
  • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.

Data Management and Annotation:

  • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
  • Handle data efficiently, ensuring its integrity throughout the workflow.
  • Engage in data relevance tasks, ensuring data sets are aligned with project goals.
  • Annotate data accurately, ensuring it adheres to set guidelines.

Quality Assurance and Analysis:

  • Conduct manual quality analysis of model results.
  • Recognize error patterns and report anomalies for further investigation.
  • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
  • Implement basic quality control measures and ensure the reliability of processed data.
  • Utilize intermediate data analysis techniques to extract insights and inform decision-making.
  • Arbitrate discrepancies effectively, ensuring consistent data quality.

Linguistic and NLP Tasks:

  • Apply basic knowledge of natural language processing and linguistics to data processing tasks.
  • Ensure linguistic accuracy in all processed and annotated data.

REQUIREMENTS

Preferred Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills

Skills & Knowledge:

  • Familiarity with command-line tools and interfaces.
  • Strong analytical skills with the ability to identify patterns and anomalies.

Additional Information:

This role primarily focuses on English US data sets; however, familiarity with translation or multi-lingual data sets can be a plus for future projects.

Additional Job Details:

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