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Internship Remote Data Labelling Jobs (NOW HIRING)

Jobsultant Solutions

Remote Data Analyst

Denver, CO · Remote

Work Environment: * 100% remote - must work in CST * 8am-5pm (9 hour day with one hour lunch break ... Own Brand (private label) reporting, recapping, tracking, and analysis, including ad-hoc analysis ...

Smart Course

Smart Course - Internship (Remote)

New York, NY · On-site +1

$16.50 - $22/hr

Examine financial data and use them to improve profitability * Manage budgets and forecasts ... research, internships, demonstrated skill) * Have a track record of success in academic and/or ...

YO AI Labs

Data Labeling Expert - Remote

New York, NY · Remote

Contractor Location: Remote Role Overview We are looking for detail-oriented Video Annotation ... The role involves accurate video labeling and structured data annotation to support AI and machine ...

New

YO AI Labs

Video Data Reviewer - Remote

New York, NY · Remote

Contractor Location: Remote Role Overview We are looking for detail-oriented Video Annotation ... The role involves accurate video labeling and structured data annotation to support AI and machine ...

New

builders

IT Internship - Remote (Summer 2027)

Irving, TX · On-site +1

This internship provides hands-on experience applying data-driven solutions to business challenges ... Assists with data analytics, data science, AI, and master data management projects in support of ...

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Internship Remote Data Labelling information

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How much do internship remote data labelling jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for internship remote data labelling in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is an internship remote data labelling?

An Internship Remote Data Labelling job involves reviewing and tagging data—such as images, text, or audio—from a remote location to help train machine learning algorithms. Interns in this role classify, annotate, or categorize raw data according to specific guidelines provided by the employer or project. This work is crucial for improving the accuracy of AI models, as properly labeled data enables better learning outcomes. Remote data labelling internships are ideal for students or recent graduates looking to gain experience in AI, data science, or related fields while working from anywhere.

What are the key skills and qualifications needed to thrive as an internship remote data labelling professional?

To excel as an Internship Remote Data Labelling professional, you need strong attention to detail, basic computer literacy, and familiarity with data annotation processes, often requiring at least a high school diploma or equivalent. Experience with data labelling platforms such as Labelbox or Supervisely, and understanding file formats like CSV or JSON, are commonly expected. Reliability, time management, and effective communication are important soft skills for remote collaboration and meeting deadlines. These competencies ensure high-quality, consistent data labelling that supports accurate machine learning model development.

What are some typical challenges faced by remote data labelling interns, and how can they be addressed?

Remote data labelling interns often encounter challenges such as managing repetitive tasks, maintaining high accuracy, and communicating effectively with team members across different time zones. To address these, it's helpful to establish a structured daily routine, regularly review quality guidelines, and use collaboration tools like Slack or Teams to stay connected. Seeking timely feedback from supervisors and participating in virtual team check-ins can also improve both efficiency and data consistency.

What is the difference between Internship Remote Data Labelling vs Data Annotation Specialist?

AspectInternship Remote Data LabellingData Annotation Specialist
CredentialsTypically students or entry-level with basic computer skillsOften requires experience or training in data annotation tools
Work EnvironmentRemote, flexible hours, internship settingRemote or on-site, professional setting
Employer & IndustryTech companies, AI startups, research projectsAI, machine learning, data services companies
Search & Comparison IntentLearning opportunity, entry-level roleProfessional data labeling work, career development

Internship Remote Data Labelling typically involves entry-level, temporary roles focused on training and learning, often suitable for students. Data Annotation Specialists are more experienced professionals performing detailed labeling tasks for ongoing projects. While both roles involve data labeling, the internship emphasizes skill development, whereas the specialist role centers on professional expertise.

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Internship Remote Data Labelling jobs near you
Infographic showing various Internship Remote Data Labelling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Video Data Labelling Expert - Remote

New York, NY • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

Full-time

Posted 2 days ago

New

Job description

Video Annotation Specialist

Job Type: Contractor
Location: Remote

Role Overview

We are looking for detail-oriented Video Annotation Specialists to review and annotate videos of robotic arms performing various tasks. The role involves accurate video labeling and structured data annotation to support AI and machine-learning projects.

Key Responsibilities
  • Review videos and identify key actions, events, and outcomes.
  • Annotate and label video content according to project guidelines.
  • Use video annotation tools to create accurate, structured datasets.
  • Maintain consistency and accuracy across annotations.
  • Collaborate with team members to resolve unclear cases.
  • Participate in quality checks and incorporate feedback.
Requirements
  • Experience in video annotation, data labeling, or similar work preferred.
  • Strong attention to detail and accuracy.
  • Familiarity with video annotation tools.
  • Good written communication and collaboration skills.
  • Strong time-management and organizational abilities.
  • Experience with AI, machine learning, or robotics projects is a plus.