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Hourly Remote Data Labeling Jobs in New York (NOW HIRING)

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 ...

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 ...

... Data teams, and external partners, the Artwork & Labeling Associate drives project execution ... This will be a remote position. RESPONSIBILITIES: D2D Project Execution & Workflow Management

Delivery Lead

New York, NY ยท Remote

$110K - $140K/yr

... and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol ... Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label ...

Data Analyst

New York, NY ยท On-site +1

$21 - $32/hr

This is a full-time remote position based in United States , offering an hourly wage of $21 - $32 ... Develop and implement databases, data collection systems, and data analytics strategies that ...

New

AI Data Engineer

Secaucus, NJ ยท Remote

$100K - $150K/yr

AI Data Engineer - Remote Bright Vision Technologies is a technology consulting and software ... Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement ...

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Hourly Remote Data Labeling information

What are the key skills and qualifications needed to thrive as an Hourly Remote Data Labeler, and why are they important?

To thrive as an Hourly Remote Data Labeler, you need strong attention to detail, basic computer literacy, and the ability to follow specific guidelines, often with a high school diploma or equivalent. Familiarity with data annotation tools and platforms such as Labelbox, Prodigy, or internal company systems is typically required. Reliability, time management, and effective written communication are crucial soft skills for meeting deadlines and maintaining quality in a remote setting. These skills and qualities are important to ensure accurate, consistent data labeling that directly impacts the performance of AI and machine learning models.

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

AspectHourly Remote Data LabelingData Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with some industry-specific knowledge
Work EnvironmentRemote, flexible hoursRemote, often project-based or ongoing
Industry UsageCommon in AI/ML developmentUsed across tech, healthcare, automotive sectors
Search IntentLooking for remote data labeling jobsSearching for data annotation roles

Both roles involve labeling or annotating data for machine learning models, often remotely. The main difference lies in terminology and specific industry usage, but they share similar credentials and work environments.

What is hourly remote data labeling?

Hourly remote data labeling is a job where individuals work from home to tag, categorize, or annotate data (such as images, videos, text, or audio) for machine learning and artificial intelligence projects. Workers are typically paid by the hour and use online platforms to complete labeling tasks assigned by companies or research organizations. This work is crucial because AI models need large volumes of accurately labeled data to learn and function properly. The job usually requires attention to detail and may involve following specific guidelines to ensure data quality.

What are some common challenges faced by hourly remote data labeling professionals, and how can they be managed?

Hourly remote data labeling professionals often encounter challenges such as maintaining consistent accuracy, managing repetitive tasks, and staying self-motivated while working independently. To manage these challenges, it's important to set up a dedicated workspace, take regular breaks to reduce fatigue, and follow established labeling guidelines closely. Frequent communication with team leads and participating in quality feedback sessions can also help ensure your work meets project standards and fosters professional growth.
What are the most commonly searched types of Remote Data Labeling jobs in New York? The most popular types of Remote Data Labeling jobs in New York are:
What cities in New York are hiring for Hourly Remote Data Labeling jobs? Cities in New York with the most Hourly Remote Data Labeling job openings:

AI/ML Data Contributor

TSMG

New York, NY โ€ข Remote

Part-time

Posted 2 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.