ZipRecruiter

Log In

2

Data Labeler Remote Jobs in New York (NOW HIRING)

TSMG

AI/ML Data Contributor

New York, NY · 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

New York, NY · 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 ...

Nestle

Artwork & Labeling Associate

Bridgewater, NJ · Remote

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

HumanSignal

Delivery Lead

New York, NY · 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 ...

Lytehaus Group

Software Engineering Intern

New York, NY · On-site +1

New York City (remote-friendly; WeWork office access available) Type: Internship, paid -- full-time ... Data pipeline work: capturing, structuring, and labeling behavioral signals from live episodes

next page

Showing results 1-20

All JobsData Labeler JobsData Labeler Remote JobsData Labeler Remote Jobs in New York

Data Labeler Remote information

Is data labeling a good career?

Data labeling is a common entry-level role in the AI and machine learning industry, involving annotating data such as images, text, or audio to train algorithms. It often offers flexible remote work options and requires attention to detail and basic technical skills. While it can provide a stepping stone into tech-related fields, it may have limited advancement opportunities without additional skills or certifications.

What are the key skills and qualifications needed to thrive as a remote data labeler?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

What are some common challenges faced by remote data labelers and how can they be managed?

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

How much do data labelers get paid?

Data labelers working remotely typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the company. Some roles may offer project-based pay or bonuses, and familiarity with labeling tools can improve earning potential.

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

What are the most commonly searched types of Data Labeler jobs in New York? The most popular types of Data Labeler jobs in New York are:
What are popular job titles related to Data Labeler Remote jobs in New York? For Data Labeler Remote jobs in New York, the most frequently searched job titles are:
What job categories do people searching Data Labeler Remote jobs in New York look for? The top searched job categories for Data Labeler Remote jobs in New York are:
What cities in New York are hiring for Data Labeler Remote jobs? Cities in New York with the most Data Labeler Remote job openings:
Data Labeler Remote jobs near you
Infographic showing various Data Labeler Remote job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 11% Part Time, and 8% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

AI/ML Data Contributor

TSMG

New York, NY • Remote

Part-time

Re-posted 10 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.