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Ai Model Jobs in Utah (NOW HIRING)

micro1 AI

Computational Biologist - AI Reviewer

Provo, UT · On-site +1

$90 - $120/hr

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. Scope of Work

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Collaborate with data scientists, ML engineers, and software teams to support AI model development, training, and deployment workflows. * Implement automation, CI/CD, DevOps, and MLOps practices to ...

Autonomous Solutions

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93K - $122K/yr

Collaborate with data scientists, ML engineers, and software teams to support AI model development, training, and deployment workflows. * Implement automation, CI/CD, DevOps, and MLOps practices to ...

Bread Financial

Lead AI Compliance Testing

Draper, UT · Hybrid

$146K/yr

Collaborate with Technology, AI/Model Risk, Enterprise Risk, Data Governance, Privacy, Legal, and business stakeholders to review AI initiatives, challenge control design, and escalate risks in ...

Zions Bank

AI Governance Manager

Midvale, UT · On-site

Familiarity with GRC tooling, AI model inventory platforms, or automated risk assessment workflows. * Familiarity with data science and machine learning concepts. * Strong analytical and problem ...

Zions Bancorporation

AI Governance Manager

Midvale, UT · On-site

Familiarity with GRC tooling, AI model inventory platforms, or automated risk assessment workflows. * Familiarity with data science and machine learning concepts. * Strong analytical and problem ...

Enterprise Services

AI Governance Manager

Midvale, UT · Hybrid

Familiarity with GRC tooling, AI model inventory platforms, or automated risk assessment workflows. * Familiarity with data science and machine learning concepts. * Strong analytical and problem ...

Awardco

Principal AI Solutions Architect

Lindon, UT · On-site

Design a stateful, multi-agent AI model and agent-to-agent (A2A) workflows, including the six micro-agents (identity, enrichment, qualification, routing, drafting, and feedback) that automate the ...

Awardco

Principal AI Solutions Architect

Lindon, UT

As Principal AI Solutions Architect, you will own the technical design of that foundation: the hub-and-spoke master data model, the event-log flow into Snowflake, and the governed APIs that let AI ...

LVT

AI Specialist

American Fork, UT

Build and deploy RAG pipelines and Cortex-based models in partnership with Data Engineering, translating business needs into production-ready AI solutions. * Architect the AI strategy at the ...

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All JobsAi Model JobsAi Model Jobs in Utah

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 Utah?

For Ai Model jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Ai Model jobs in Utah look for?

The top searched job categories for Ai Model jobs in Utah are:

What cities in Utah are hiring for Ai Model jobs?

Cities in Utah with the most Ai Model job openings:

Ai Model jobs near you
Infographic showing various Ai Model job openings in Utah as of August 2026, with employment types broken down into 2% Internship, 68% Full Time, 14% Part Time, and 16% Contract. Highlights an 72% In-person, and 28% Remote job distribution.

Computational Biologist - AI Reviewer

micro1 AI

Provo, UT • On-site, Remote

$90 - $120/hr

Part-time

Posted 18 days ago

Job description

Role Title: Computational Biology Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic 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 — your domain knowledge is what matters.


Scope of Work

  1. Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry.
  2. Provide feedback and domain-specific insights to improve AI models in computational biology contexts.
  3. Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with industry standards.
  4. Develop and review problem sets, case studies, or scenarios based on real-world medicinal chemistry challenges.
  5. Collaborate asynchronously with other experts to validate findings and share perspectives on project deliverables.
  6. Contribute to the refinement of data curation methodologies and best practices in computational biology.


Preferred Qualifications

  1. Advanced degree (PhD, PharmD, or MSc) in computational biology, medicinal chemistry, bioinformatics, or a closely related field.
  2. Demonstrated expertise in medicinal chemistry, including experience with drug discovery or design.
  3. Strong analytical skills with a deep understanding of biological datasets and scientific literature.
  4. Experience applying computational methods to solve problems in chemistry or biology.
  5. Proficiency with relevant bioinformatics tools, cheminformatics platforms, or data analysis software.
  6. Excellent written communication skills to clearly explain complex scientific concepts to diverse audiences.
  7. Previous participation in cross-disciplinary or AI-driven scientific projects is a plus.

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