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Full Time Ai Data Annotation Jobs in Chicago, IL

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 ...

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 ...

The AI Quality Analyst is a critical role responsible for ensuring the performance, safety, and ... This includes performing data annotation and validation to ensure the integrity of our ground-truth ...

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Full Time Ai Data Annotation information

What is a full time AI data annotation job?

Full Time AI Data Annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Annotators play a crucial role in ensuring AI systems understand and process information accurately by providing high-quality, human-curated data. These positions usually require attention to detail, basic computer skills, and the ability to follow specific guidelines for different projects. Full-time roles typically offer stable hours and may be remote or on-site, depending on the employer.

What are the key skills and qualifications needed to thrive as a full time AI data annotation specialist?

To thrive as a Full Time AI Data Annotation Specialist, you need strong attention to detail, basic data literacy, and often a high school diploma or equivalent. Familiarity with annotation platforms (like Labelbox or Supervisely) and understanding of data labeling guidelines are typically required. Patience, consistency, and effective communication are soft skills that help ensure accuracy and clarity in collaborative projects. These skills and qualities are crucial for producing high-quality labeled data, which directly impacts the performance of AI models.

What are some common challenges faced by full time AI data annotation professionals, and how can they be addressed?

AI Data Annotation professionals often encounter challenges such as maintaining high accuracy while working with large datasets, interpreting ambiguous data, and consistently following complex labeling guidelines. These challenges can be addressed through thorough training, frequent communication with project managers or data scientists, and utilizing annotation tools with built-in quality checks. Collaboration with team members and regular feedback sessions also help ensure consistency and improve overall data quality, making the annotation process smoother and more efficient.

What is the difference between Full Time Ai Data Annotation vs Data Labeler?

AspectFull Time Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal technical requirements
Work EnvironmentOffice or remote; part of AI development teamsOffice or remote; often task-based or freelance
Industry UsageUsed across AI, machine learning, and data science industriesPrimarily in AI and machine learning industries for data preparation
Job ScopeFull-time, with responsibilities including data annotation, quality control, and collaborationTask-specific, focusing on labeling data accurately for AI training

Full Time Ai Data Annotation roles typically require more consistent hours, team collaboration, and a broader scope of responsibilities compared to Data Labelers, who often work on individual tasks with minimal oversight. Both roles are essential in AI development, but Full Time Ai Data Annotation offers more stability and integration within AI projects.

What are the most commonly searched types of Ai Data Annotation jobs in Chicago, IL?

The most popular types of Ai Data Annotation jobs in Chicago, IL are:

What are popular job titles related to Full Time Ai Data Annotation jobs in Chicago, IL?

For Full Time Ai Data Annotation jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Full Time Ai Data Annotation jobs in Chicago, IL look for?

The top searched job categories for Full Time Ai Data Annotation jobs in Chicago, IL are:

Infographic showing various Full Time Ai Data Annotation job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

AI/ML Data Contributor

TSMG

Chicago, IL โ€ข On-site

Full-time

Re-posted 29 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.
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