1

Data Labelling Jobs in Wisconsin (NOW HIRING)

... labeling * Maintain and manage product master data within SAP and participate in workflows for new ... products and product changes * Partner with crossfunctional stakeholders across Quality Assurance ...

Utilize BarTender software to generate and print compliant GHS labels and variable data labels as required. * Perform other duties and special projects as assigned. Additional Requirements:

Utilize BarTender software to generate and print compliant GHS labels and variable data labels as required. * Perform other duties and special projects as assigned. Additional Requirements:

Cyber Data Protection Manager

Milwaukee, WI · Remote

$109K - $147K/yr

DLP, sensitivity labels, data classification, DSPM, DSPM for AI, on-demand classification, or related Microsoft 365 data security capabilities * Knowledge of AI security and governance concepts ...

next page

Showing results 1-20

Data Labelling information

What does a data labeler do?

A data labeler is responsible for annotating and categorizing data such as images, videos, or text to help train machine learning models. They use tools and guidelines to ensure accurate labeling, which is essential for developing reliable AI systems. Attention to detail and understanding of the data are important for this role.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can offer flexible schedules and opportunities to develop skills in AI and data management, but typically involves repetitive tasks and lower pay compared to more advanced tech roles.

What is a Data Labelling job?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What is the job description of data labeling?

Data labeling involves annotating or tagging data such as images, text, or videos to help machine learning models understand and learn from the data. The role requires attention to detail, familiarity with labeling tools, and adherence to guidelines to ensure high-quality annotations for AI training. It is often performed remotely and may involve repetitive tasks with a focus on accuracy.

What are the typical daily responsibilities of a Data Labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the Data Labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools like Labelbox or CVAT and understand data privacy requirements. Basic skills in image, text, or audio annotation are helpful, and some roles may require attention to detail and the ability to follow guidelines. Entry-level positions often provide training, making it accessible for beginners.
What are the most commonly searched types of Data Labelling jobs in Wisconsin? The most popular types of Data Labelling jobs in Wisconsin are:
What are popular job titles related to Data Labelling jobs in Wisconsin? For Data Labelling jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Labelling jobs in Wisconsin look for? The top searched job categories for Data Labelling jobs in Wisconsin are:
Infographic showing various Data Labelling 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.
Video Field Collector - AI Training Data

Video Field Collector - AI Training Data

micro1 AI

Green Bay, WI • Remote

$13/hr

Part-time

Posted 20 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.