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Part Time Data Labeling Jobs (NOW HIRING)

Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing language-based assignments, and helping improve AI systems. Requirements: * Fluent or native-level ...

Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing language-based assignments, and helping improve AI systems. Requirements: * Fluent or native-level ...

Tasks may include reviewing AI-generated content, evaluating responses, labeling data, completing language-based assignments, and helping improve AI systems. Requirements: * Fluent or native-level ...

AST SpaceMobile is seeking an AI Data Operations Manager based in Midland, TX to operate, secure ... You will hire, train, schedule, and supervise a part-time labeling workforce on AST's in-house ...

AST SpaceMobile is seeking an AI Data Operations Manager based in Midland, TX to operate, secure ... You will hire, train, schedule, and supervise a part-time labeling workforce on AST's in-house ...

Research Coordinator

New York, NY · On-site

$52K - $65K/yr

Hunt Lab is seeking a part-time scientific Research Coordinator position for a project focused on ... Ensure proper versioning and data labeling for easy accessibility. * Assist project staff in ...

This is a Full-Time Role (40 hours per week, 5 days per week) with no option for part-time work ... Improve data labelling and documentation for AI usage About You * A BA/BS in Computer Science ...

New

This is a Full-Time Role (40 hours per week, 5 days per week) with no option for part-time work ... Improve data labelling and documentation for AI usage About You * A BA/BS in Computer Science ...

New

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Part Time Data Labeling information

What is a part time data labeling job?

Part time data labeling jobs involve annotating or tagging data—such as images, audio, text, or video—which is then used to train machine learning models. These roles typically require you to review data and apply labels or classifications based on specific guidelines. The work is often flexible, can be done remotely, and usually does not require advanced technical skills. Data labelers play a crucial role in ensuring AI systems learn from accurate, high-quality data. Tasks may include identifying objects in images, transcribing audio, or categorizing text.

What is the difference between Part Time Data Labeling vs Part Time Data Annotation?

AspectPart Time Data LabelingPart Time Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or flexible, often freelanceRemote or flexible, often freelance
Industry UsageCommon in AI/ML projects for image, text, audio dataUsed interchangeably with data labeling, often in similar contexts

Part Time Data Labeling and Part Time Data Annotation are often used interchangeably, focusing on preparing data for machine learning models. Both roles require similar skills and work environments, primarily involving labeling or annotating data such as images, text, or audio. The main difference is terminology preference, but they serve the same purpose in AI data preparation processes.

What are the key skills and qualifications needed to thrive as a part time data labeling specialist?

To thrive as a Part Time Data Labeling Specialist, you need strong attention to detail, basic computer literacy, and the ability to follow specific guidelines or protocols. Familiarity with data annotation tools, spreadsheet software, and platforms like Labelbox or Amazon SageMaker Ground Truth is often required. Reliability, consistency, and effective communication are valuable soft skills for ensuring high-quality, accurate work. These skills are essential because precise data labeling is foundational to training effective machine learning models and ensuring project success.

What are the typical challenges faced by part-time data labelers, and how can they be managed?

Part-time data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring accuracy while labeling large volumes of data, and adapting to evolving project guidelines. To manage these, it's helpful to take regular breaks to reduce fatigue, double-check work for consistency, and stay updated on any changes in labeling instructions. Collaboration with team leads or participating in team discussions can also clarify doubts and improve the overall quality of the work.
More about Part Time Data Labeling jobs
What cities are hiring for Part Time Data Labeling jobs? Cities with the most Part Time Data Labeling job openings:
What are the most commonly searched types of Data Labeling jobs? The most popular types of Data Labeling jobs are:
Infographic showing various Part Time Data Labeling job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Video Data Annotator - Contract

Hooglee

San Francisco, CA • On-site

$25/hr

Part-time

Re-posted 9 days ago


Job description

Video Data Annotator (Contract) - On-Site
Location: San Francisco, On-site
Compensation: $25/hour
Schedule: Part-time (4-8 hours per day)
Duration: 10-week engagement to start
We are looking for a Video Data Annotator (Contract) to support our AI Team.
This is an on-site role. A device will be provided in the office.
Program Overview
  • 10-week initial engagement
  • Opportunity to transition to full-time based on team needs and performance
What You'll Do
  • Watch and annotate video data across different formats
  • Label and evaluate video content with high accuracy
  • Provide feedback on video quality and questionnaire setup to the AI Team
  • Communicate clearly about edge cases, inconsistencies, or improvements
Must-Have Qualifications
  • Strong attention to detail
  • Strong English reading, writing, and speaking skills
Nice-to-Have
  • Prior data labeling or annotation experience

If you're detail-oriented, comfortable working with video content, and excited to contribute to AI model development, we'd love to hear from you.