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Internship Remote Data Annotation Jobs in Philadelphia, PA

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

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$12

$22

$42

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

As of May 28, 2026, the average hourly pay for internship remote data annotation in Philadelphia, PA is $22.71, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $24.76 per hour, depending on experience, location, and employer.

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

To thrive as a Remote Data Annotation Intern, you need attention to detail, basic data processing skills, and familiarity with labeling guidelines, generally supported by a high school diploma or relevant coursework. Experience with annotation platforms, spreadsheets, and sometimes basic programming tools or machine learning frameworks is often required. Strong communication, time management, and the ability to follow precise instructions are valuable soft skills in this role. These skills ensure high-quality, accurate data labeling, which is critical for training reliable machine learning models.

What typical tasks can I expect to handle as a remote data annotation intern, and how is performance usually evaluated?

As a remote data annotation intern, your primary tasks will involve reviewing and labeling data—such as images, text, or audio—according to specific guidelines provided by your team. You'll likely work with annotation tools, follow detailed instructions to ensure high-quality and consistent labeling, and may participate in quality assurance checks. Performance is generally evaluated based on annotation accuracy, speed, and your ability to follow instructions, with regular feedback provided via virtual meetings or project management platforms. Effective communication and attention to detail are key to succeeding in this collaborative, remote environment.

What is a remote data annotation internship?

A remote data annotation internship is a temporary position where interns work from home or another remote location to label, categorize, or tag data such as images, text, or audio. This annotated data is often used to train machine learning models and improve artificial intelligence systems. Interns typically use specialized platforms or tools to complete their tasks, and gain hands-on experience in data handling, quality control, and understanding AI workflows. The internship is ideal for those interested in technology, data science, or AI, and often requires strong attention to detail and good communication skills.

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

AspectInternship Remote Data AnnotationData Labeling Specialist
CredentialsTypically students or entry-level with basic computer skillsRelevant experience or certifications in data annotation or related fields
Work EnvironmentRemote, flexible hours, often part-timeRemote or on-site, depending on employer, often full-time
Industry UsageCommon in AI/ML projects, tech companies, research institutionsUsed in AI/ML, autonomous vehicles, healthcare, and tech sectors

Internship Remote Data Annotation roles are usually entry-level, temporary positions aimed at gaining experience, while Data Labeling Specialists are more experienced roles focused on accurately annotating data for machine learning models. Both roles are essential in AI development but differ in experience requirements and job scope.

What are the most commonly searched types of Remote Data Annotation jobs in Philadelphia, PA? The most popular types of Remote Data Annotation jobs in Philadelphia, PA are:
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Internship Remote Data Annotation jobs near you

AI/ML Data Contributor

TSMG

Philadelphia, PA • Remote

Full-time

Posted 29 days ago

Job description

Project Overview
We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing.

Projects may vary in scope and format, offering both remote and in-person opportunities (such as device or VR testing). This is a flexible, task-based role with the opportunity to participate in multiple projects over time.

Responsibilities
  • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation
  • Participate in remote assignments or attend on-site sessions when required
  • Follow project guidelines and ensure high-quality task completion
  • Provide feedback and input during testing activities
  • Complete tasks within given timelines
Requirements
  • Must be based in the United States
  • Strong attention to detail and ability to follow instructions
  • Basic computer skills and familiarity with digital tools
  • Reliable internet connection and access to a computer or smartphone
  • Availability to participate in task-based work (schedule may vary)
Nice to Have
  • Previous experience in data annotation, QA, or testing
  • Interest in AI, machine learning, or emerging technologies
What We Offer
  • Paid, flexible task-based work
  • Opportunity to work on innovative AI/ML projects
  • Exposure to cutting-edge technologies (including device and VR testing)
  • Potential for ongoing project participation

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.