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Ai Model Jobs in Kansas (NOW HIRING)

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:

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:

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:

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:

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Ai Model information

What is the difference between Ai Model vs Data Scientist?

AspectAi ModelData Scientist
Required CredentialsKnowledge of machine learning, programming skills, sometimes certifications in AI/MLDegree in data science, statistics, computer science; certifications beneficial
Work EnvironmentFocus on developing, training, and deploying AI modelsData analysis, interpretation, and visualization; often collaborates with AI teams
Industry UsageUsed in AI development, automation, and predictive modelingApplied across industries for insights, reporting, and decision-making

While both roles involve working with data and algorithms, an Ai Model primarily focuses on creating and refining AI systems, whereas a Data Scientist analyzes data to generate insights and supports AI development. The roles often overlap but serve distinct functions within the data and AI ecosystem.

What are some common challenges faced by professionals working as AI model developers, and how can they address them?

Professionals working as AI Model developers often encounter challenges such as managing large and complex datasets, ensuring model accuracy, and addressing issues of bias in algorithms. They may also need to balance the trade-off between model performance and interpretability, especially when deploying models in production environments. To overcome these challenges, AI Model developers typically collaborate closely with data engineers, domain experts, and other stakeholders, regularly validate their models, and stay updated with the latest advancements in the field to adopt best practices.

What is an AI model?

AI models are computer programs designed to simulate human intelligence by learning patterns from data and making predictions or decisions based on that learning. These models can perform a variety of tasks, such as recognizing speech, translating languages, analyzing images, and generating text. AI models are created using machine learning algorithms and are trained on large datasets to improve their accuracy and performance. Popular examples include neural networks, decision trees, and support vector machines. The effectiveness of an AI model depends on the quality of the data, the chosen algorithm, and the training process.

What are the key skills and qualifications needed to thrive as an AI model, and why are they important?

To excel as an AI Model Developer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with ML frameworks like TensorFlow or PyTorch, cloud platforms, and relevant certifications such as TensorFlow Developer or AWS Machine Learning Specialty are valuable. Critical thinking, continuous learning, and effective collaboration with interdisciplinary teams are key soft skills for success. These competencies enable the creation of accurate, reliable AI models that can effectively solve complex real-world problems.

How to get into AI modeling?

To become an AI modeler, develop strong skills in programming languages like Python, learn machine learning frameworks such as TensorFlow or PyTorch, and gain experience with data preprocessing and model training. A background in computer science, mathematics, or related fields, along with relevant certifications or courses, can also improve your prospects.
What are popular job titles related to Ai Model jobs in Kansas? For Ai Model jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Ai Model jobs in Kansas look for? The top searched job categories for Ai Model jobs in Kansas are:
Infographic showing various Ai Model job openings in Kansas as of July 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 60% In-person, 7% Hybrid, and 33% Remote job distribution.

AI Trainer - Microbiology Expert

micro1 AI

Topeka, KS โ€ข Remote

$70 - $90/hr

Part-time

Posted 8 days ago


Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. 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 โ€” your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelorโ€™s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Masterโ€™s or PhD) in a relevant field.