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Data Labelling Jobs in Wisconsin (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

In this role, you will set up and operate a narrow-web flexographic Mark Andy press to print pressure-sensitive labels, peel-and-reseal labels, and variable data labels. You will be responsible for ...

Printing Press Utility Operator

Neenah, WI · On-site

$22.25 - $29.25/hr

Outlook Group prints pressure-sensitive labels, peel and reseal labels and variable data labels. You will be working with custom product packaging and printing labels, shrink sleeves, flexible ...

Previous food safety and labeling experience is required, preferably in a food processing ... Message and data rates may apply. Text STOP to opt out or HELP for help. Terms and conditions:

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Data Labelling information

What is a data labelling?

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 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 and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

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 provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.

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:

Infographic showing various Data Labelling job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

AI/ML Data Contributor

Milwaukee, WI

Full-time

Re-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.