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Remote Content Labelling 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 ...

AEG Presents

Procurement Intern

Conshohocken, PA · On-site +1

$17.75 - $23.75/hr

... our white-label approach. Our network of 450 venues worldwide, hosting 20,000 events and ... content & booking - of world-class live events and venues. The Legends Global culture is one of ...

AEG Presents

Procurement Intern

Conshohocken, PA · On-site +1

$17.75 - $23.75/hr

... our white-label approach. Our network of 450 venues worldwide, hosting 20,000 events and ... content & booking - of world-class live events and venues. The Legends Global culture is one of ...

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All JobsRemote Content Labelling JobsRemote Content Labelling Jobs in Philadelphia, PA

Remote Content Labelling information

See Philadelphia, PA salary details

$29.8K

$117.7K

$130.2K

How much do remote content labelling jobs pay per year?

As of May 28, 2026, the average yearly pay for remote content labelling in Philadelphia, PA is $117,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,100.00 and $129,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Content Labeller, and why are they important?

To thrive as a Remote Content Labeller, you need strong attention to detail, analytical thinking, and familiarity with content guidelines, typically supported by a high school diploma or equivalent. Experience with content management systems, annotation tools, and sometimes specific training on labeling protocols is often required. Excellent communication, time management, and the ability to work independently are valuable soft skills for this role. These skills ensure accurate and consistent labeling, which is critical for training AI systems and maintaining content quality at scale.

What are some common challenges faced in remote content labelling roles and how can they be managed?

Remote content labellers often encounter challenges such as maintaining focus during repetitive tasks, managing ambiguous guidelines, and ensuring consistent quality across large datasets. To address these, it's helpful to establish a structured daily routine, actively participate in team discussions or feedback sessions, and utilize available resources for clarification on guidelines. Collaborating with team leads and other labellers through chat platforms also helps in resolving uncertainties efficiently and maintaining high accuracy standards.

What is remote content labelling?

Remote content labelling is the process of identifying, tagging, or classifying various types of digital content—such as images, videos, text, or audio—from a remote location, typically from home. This work is crucial for training machine learning algorithms and improving artificial intelligence systems, as labelled data helps computers understand and process information. Remote content labellers use specific guidelines and tools provided by their employer or client to ensure consistency and accuracy. The job often requires attention to detail, good communication skills, and the ability to follow instructions closely.

What is the difference between Remote Content Labelling vs Remote Data Annotation?

AspectRemote Content LabellingRemote Data Annotation
Primary FocusLabeling and categorizing content such as images, videos, and text for machine learningAdding detailed annotations to data to improve model accuracy, often including bounding boxes, segmentation, or key points
Skills RequiredAttention to detail, understanding of content types, basic data handlingTechnical skills, familiarity with annotation tools, precision in marking data
Work EnvironmentRemote, flexible hours, often part-time or freelanceRemote, similar flexible setup, often within AI or ML projects

Both roles involve working remotely to prepare data for AI models, but Content Labelling primarily involves categorizing content, while Data Annotation requires detailed technical markings. Understanding these differences helps job seekers find the right fit for their skills and career goals.

What are popular job titles related to Remote Content Labelling jobs in Philadelphia, PA? For Remote Content Labelling jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Remote Content Labelling jobs in Philadelphia, PA look for? The top searched job categories for Remote Content Labelling jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Remote Content Labelling jobs? Cities near Philadelphia, PA with the most Remote Content Labelling job openings:
Remote Content Labelling 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.