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Data Annotation No Experience Needed Jobs in Park Ridge, IL

TSMG

AI/ML Data Contributor

Chicago, IL

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL · On-site

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 ...

TSMG

AI/ML Data Contributor

Chicago, IL

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 ...

Arrive Logistics

Data Scientist II

Chicago, IL · On-site

$138 - $172/hr

... business needs into concrete technical approaches, and communicates findings clearly to both ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

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Data Annotation No Experience Needed information

What is data annotation?

Data annotation is the process of labeling or tagging data, such as images, text, or audio, to help train artificial intelligence and machine learning models. Many data annotation jobs require little to no prior experience, as employers often provide training on the specific tools and guidelines needed for the work. These jobs are ideal for beginners looking to enter the tech field, as they typically require attention to detail and basic computer skills. With consistent work, data annotators can build valuable experience for more advanced roles in data science and AI.

What is the difference between Data Annotation No Experience Needed vs Data Labeler?

AspectData Annotation No Experience NeededData Labeler
Required CredentialsNo prior experience or certifications typically requiredOften similar, minimal credentials needed
Work EnvironmentRemote or office-based, flexible hoursPrimarily remote, task-based work
Industry UsageCommon in AI, machine learning, and data processing companiesUsed in AI, autonomous vehicles, and tech sectors
Search & Comparison IntentPeople seeking entry-level data annotation rolesIndividuals comparing entry-level data labeling jobs

Data Annotation No Experience Needed and Data Labeler roles are similar, both requiring minimal or no prior experience. They are commonly found in AI and machine learning industries, often offering remote work. The main difference lies in terminology; 'Data Labeler' is a more specific job title within data annotation tasks. Both roles are suitable for beginners looking to start a career in data processing and AI training.

What does a typical workday look like for someone starting out in data annotation with no prior experience?

For those new to data annotation, a typical workday involves reviewing and labeling large sets of data—such as images, audio, or text—according to specific guidelines provided by the employer or client. You’ll likely work as part of a remote or distributed team, using specialized software tools to complete your tasks. While the work is often independent, you may participate in occasional team meetings or training sessions to clarify guidelines and improve accuracy. Consistency and attention to detail are crucial, and feedback from supervisors will help you refine your skills. Over time, demonstrating accuracy and reliability can open opportunities for more complex projects or advancement within the team.

What are the key skills and qualifications needed to thrive as a data annotation specialist with no prior experience?

To thrive as a Data Annotation specialist with no prior experience, attention to detail, basic computer literacy, and the ability to follow guidelines are essential. Familiarity with annotation tools or platforms (such as Labelbox or SuperAnnotate) and basic understanding of data privacy protocols are often required. Strong organizational skills, patience, and clear communication help individuals excel in repetitive tasks and collaborate with team members or project leads. These skills and qualities are critical for maintaining high data quality and ensuring annotated datasets are accurate for downstream machine learning applications.
What job categories do people searching Data Annotation No Experience Needed jobs in Park Ridge, IL look for? The top searched job categories for Data Annotation No Experience Needed jobs in Park Ridge, IL are:
What cities near Park Ridge, IL are hiring for Data Annotation No Experience Needed jobs? Cities near Park Ridge, IL with the most Data Annotation No Experience Needed job openings:
Data Annotation No Experience Needed jobs near you
Infographic showing various Data Annotation No Experience Needed job openings in Park Ridge, IL as of August 2026, with employment types broken down into 45% Full Time, and 55% Part Time. Highlights an 82% In-person, and 18% Remote job distribution.

AI/ML Data Contributor

TSMG

Chicago, IL

Part-time

Re-posted 14 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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