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Data Annotation For Ai Jobs in Kansas (NOW HIRING)

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

Wichita, KS · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

WellSky

Data Scientist

Overland Park, KS · On-site

The Data Scientist role focuses on turning clinical conversations into accurate, useful ... for AI/ML or LLM systems (accuracy metrics, human review, annotation, error analysis). • ...

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All JobsData Annotation For Ai JobsData Annotation For Ai Jobs in Kansas

Data Annotation For Ai information

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a Data Annotation Specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.
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What cities in Kansas are hiring for Data Annotation For Ai jobs? Cities in Kansas with the most Data Annotation For Ai job openings:
Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Kansas as of July 2026, with employment types broken down into 80% Full Time, 18% Part Time, and 2% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

AI/ML Data Contributor

TSMG

Wichita, KS

Part-time

Re-posted 20 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.