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Data Labeler Remote Jobs in Wisconsin (NOW HIRING)

micro1 AI

First-Person AI Video Trainer

Green Bay, WI · Remote

$13/hr

Data-Video Generalist Job Type: Contractor Location: Remote - experts based in Alabama, Arkansas ... Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and ...

micro1 AI

First-Person AI Video Trainer

Milwaukee, WI · Remote

$13/hr

Data-Video Generalist Job Type: Contractor Location: Remote - experts based in Alabama, Arkansas ... Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and ...

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Data Labeler Remote information

Is data labelling a good career?

Data labeling is an entry-level role that involves annotating data for machine learning models, often requiring attention to detail and basic technical skills. It can provide a stepping stone into the tech industry, but it typically offers limited advancement opportunities and lower pay compared to more specialized roles. Many professionals use it as initial experience before moving into data science or related fields.

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

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.

How can I make 2000 a week working from home?

A remote data labeler can potentially earn around $2000 per week by working full-time hours, often 40 hours or more, and gaining experience or specializing in high-demand data annotation tasks. Increasing earnings may involve working for multiple clients, improving skills with annotation tools, or taking on higher-paying projects, but consistent high weekly income depends on workload, rates, and efficiency.

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.

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.

How much are data labelers paid?

Data labelers working remotely typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer project-based pay or bonuses for accuracy and efficiency.

Is data labeling work from home?

Data labelers often work remotely, as the job typically involves reviewing and annotating data using a computer and internet connection. Many companies offer remote data labeling positions with flexible schedules, requiring basic computer skills and attention to detail.
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Data Labeler Remote jobs near you
Infographic showing various Data Labeler Remote job openings in Wisconsin as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
AI Data Collector - Computer Vision (Remote/Contract)

AI Data Collector - Computer Vision (Remote/Contract)

micro1 AI

Madison, WI • Remote

$13/hr

Part-time

Posted 10 days ago

Job description

Job Title: Data-Video Generalist


Job Type: Contractor


Location: Remote - experts based in Alabama, Arkansas, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, Montana, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Virginia, West Virginia, and Wisconsin.


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Capture precise motion data using your smartphone during specified physical tasks.
  2. Supported devices include the iPhone 12 and later, Google Pixel 6 and later, and Samsung Galaxy S21 and later.
  3. Record synchronized video footage to validate and enhance the integrity of collected sensor data.
  4. Follow detailed technical protocols to ensure all submissions meet strict quality, labeling, and determinism standards.
  5. Consistently contribute a minimum of 10 hours of approved video data per week throughout the project duration.
  6. Communicate effectively with the team to clarify guidelines and provide feedback on data collection processes.
  7. Ensure timely and reliable delivery of data outputs in accordance with project milestones.
  8. Participate in required device compatibility checks and a custom AI-enabled interview process.


Required Skills and Qualifications:

  1. Access to a head strap to be able to record both hands within 48 hours of the start date.
  2. Demonstrated adherence to standardized protocols and rigorous technical instructions.
  3. Proven ability to manage and deliver reliable output in a fast-paced, data-driven environment.
  4. Strong written and verbal communication skills; ability to document work and collaborate remotely.
  5. Experience with mobile devices and a high level of digital literacy.
  6. Physical capability to perform repetitive movement tasks safely and accurately.
  7. Access to a compatible smartphone for high-fidelity sensor and video data collection.
  8. Eligibility to work in designated U.S. states.
  9. Note: Applications submitted with a Gmail address are strongly preferred for seamless tool integration.


Compensation Structure

Compensation is output-based; experts are paid per recorded video that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow.


Start Timeline & Availability

We typically fill roles within 48 hours, so we’re looking for teammates who are ready to jump in. If selected, we’d love for you to start your first task as soon as you move forward with your application. The expectation is to begin within ~24 hours of completing onboarding.


Equipment Requirements

Mobile:

Tasks for this project must be performed from a mobile device (smartphone). Experts will record their workflow directly from the mobile device while completing tasks.


Head Strap / Wearable: Tasks for this project must be performed using a head-mounted camera (head strap setup). Experts will record first-person video of physical tasks. The required head strap and any accompanying equipment specifications will be shared during onboarding.

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