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Full Time Online Data Annotation Jobs (NOW HIRING)

Welocalize, Inc.

OR

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

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 ...

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 ...

Apple

Senior Manager - AI Data Operations

Austin, TX

Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is ... Description You will lead an organization of internal domain experts, building scalable annotation ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... full-time experience building reliable backend systems • Experience with Linux and command line ... data annotation and dataset management tools. Company : Figure is an AI robotics company that ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$150K - $350K/yr

Experience building data annotation and dataset management tools. The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may ...

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All JobsFull Time Online Data Annotation Jobs

Full Time Online Data Annotation information

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

To thrive as a Full Time Online Data Annotation Specialist, you need strong attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency with data annotation tools, cloud-based platforms, and sometimes knowledge of scripting languages like Python is commonly required. Strong communication, time management, and the ability to work independently help individuals excel in this remote role. These skills ensure accurate, high-quality data labeling that is crucial for training effective machine learning models.

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

AspectFull Time Online Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote, online platform-basedRemote or in-office, often on specific projects
Industry UsageAI, machine learning, autonomous vehiclesAI, computer vision, NLP projects
Search IntentFull Time Online Data Annotation vs Data Labeling Specialist

Full Time Online Data Annotation involves ongoing, remote work focused on labeling data for AI training, often with a full-time schedule. Data Labeling Specialists may perform similar tasks but can work part-time or on specific projects. Both roles require attention to detail and basic technical skills, but Full Time Online Data Annotation typically offers more stability and consistent hours.

What are some common challenges faced by full-time online data annotators, and how can they be managed effectively?

Full-time online data annotators often encounter challenges such as maintaining focus during repetitive tasks, managing high volumes of data, and ensuring consistency in labeling. To address these, it's important to take regular breaks, utilize productivity tools, and follow detailed annotation guidelines closely. Many organizations provide quality checks and feedback, which can help annotators improve accuracy and efficiency over time. Additionally, collaborating with team leads or peers can offer support and clarify any uncertainties regarding complex data.

What is a Full Time Online Data Annotation job?

A Full Time Online Data Annotation job involves labeling, tagging, or categorizing data such as images, audio, video, or text to help train artificial intelligence (AI) models. Data annotators work remotely, often using specialized software platforms to accurately mark data according to specific guidelines. This role is essential for improving the accuracy and performance of machine learning algorithms in various industries, including technology, healthcare, and autonomous vehicles. Full-time positions typically require consistent hours and may offer benefits depending on the employer. Attention to detail and the ability to follow instructions are crucial skills for success in this job.
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Full Time Online Data Annotation jobs near you
Infographic showing various Full Time Online Data Annotation job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.
Data Quality Analyst

Data Quality Analyst

Welocalize, Inc.

OR

Full-time

Posted 18 days ago

Welocalize rating

7.2

Company rating: 7.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

204th of 426 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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