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Artificial Intelligence Machine Learning Engineer Jobs in Utah

... Artificial Intelligence and Robotics preferred - Designing, training, and deploying machine ... learning models - Developing scalable, cloud-native microservices using Docker and Kubernetes ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Artificial Intelligence and Robotics preferred - Demonstrating exceptional team leadership ...

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Artificial Intelligence Machine Learning Engineer information

See Utah salary details

$28.7K

$117.2K

$176.2K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for artificial intelligence machine learning engineer in Utah is $117,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $141,100.00 per year, depending on experience, location, and employer.

What is an Artificial Intelligence Machine Learning Engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by Artificial Intelligence Machine Learning Engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Utah? For Artificial Intelligence Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Utah look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities in Utah with the most Artificial Intelligence Machine Learning Engineer job openings:
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Utah as of May 2026, with employment types broken down into 94% Full Time, 4% Part Time, 1% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $117,228 per year, or $56.4 per hour.
MBSE Engineer with Security Clearance

MBSE Engineer with Security Clearance

KBR

Clearfield, UT

Other

Posted 3 days ago


KBR rating

8.3

Company rating: 8.3 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

94th of 352 rated engineering


Job description

Title:
MBSE Engineer Justification The Senior Digital Engineering position is required to support the development, implementation, and sustainment of a scalable Digital Engineering Environment (DEE) that enables standardized, model-based systems engineering practices across multiple programs, organizations, and mission domains. This role provides the technical leadership necessary to establish authoritative digital architectures, integrated digital threads, and enterprise-level MBSE processes using UAF, SysML, and advanced modeling platforms such as Cameo Systems Modeler, Teamwork Cloud, and Cameo Collaborator. The position is critical to defining scalable modeling governance, automated validation frameworks, configuration management processes, reporting automation, and collaborative engineering workflows required to maintain model integrity, traceability, and consistency across distributed engineering teams operating within secure and air-gapped environments. This role is also essential to advancing enterprise digital transformation objectives through the integration of mission engineering, Agile systems engineering, digital thread capabilities, and AI/ML-enabled engineering methodologies into the organization's engineering lifecycle processes. The position ensures alignment with corporate Digital Engineering standards while improving engineering efficiency, architecture maturity, requirements quality, and cross-organizational collaboration. Without this capability, the organization risks inconsistent model development practices, reduced engineering interoperability, limited scalability of MBSE adoption, degraded configuration control, and diminished ability to support enterprise-level systems engineering modernization initiatives and future mission capability development. Responsibilities This role will focus on implementing cutting-edge MBSE processes, advancing Digital Threads, integrating Artificial Intelligence/Machine Learning (AI/ML) methodologies, and modernizing engineering and operational processes across the organization. The ideal candidate will be a technical leader with expertise in systems engineering, hands-on application of digital transformation, and organizational change. Key Responsibilities * Lead development of platform architecture models using the Unified Architecture Framework (UAF), leveraging advanced modeling and visualization tools.
* Develop and integrate mission and mission engineering threads to support end-to-end system capability analysis.
* Champion configuration management, version control, and rigorous baselining for multiple models operating in air-gapped environments.
* Design, implement, and enforce model styling rules and automated validation suites to ensure consistency and quality in all deliverables.
* Develop custom report generation templates using Velocity Template Language (VTL) to produce documents and presentations in MS Word, PowerPoint, and Excel.
* Drive collaborative and agile systems engineering processes across multiple organizations, resulting in mature, validated platform architectures and comprehensive requirements baselines.
* Serve as a subject matter expert in MBSE methodologies, including modeling languages (UAF, SysML) and tools such as Cameo Systems Modeler, Teamwork Cloud, and Cameo Collaborator.
* Utilize the Atlassian toolset (Confluence, Jira) to facilitate Agile project management and model development.
* Lead the program-wide adoption of model-based practices, ensuring alignment with corporate digital engineering standards and best practices.
* Participate in a cross-organization MBSE community of practice, providing thought leadership and mentoring to elevate modeling quality and accelerate development velocity.
Required Qualifications: * Bachelor's Degree in science, engineering, math, computer science, or other technical discipline
* Systems Engineering experience with Model-Based Engineering applications and technology
* Intermediate knowledge and experience with System Modeling Language (SysML)
* Object-Oriented Design and Analysis experience either in system model development or programming language
* Requires an understanding of systems engineering and of model-based methodologies
* Experience with Cameo, SparxEA, or Rhapsody tool suites
* must have active TS/SCI Clearance Desired Qualifications: * Java, JavaScript, or Python programming experience
* Knowledge of engineering analysis and analytical simulation tools such as ModelCenter, Systems Toolkit (STK), Mathematica, Modelica, SciPy, or SciKit-Learn
* Knowledge of multi-domain analysis and optimization techniques and tool
* Knowledge of Unified Architecture Framework (UAF)
* Experience with the development of executable systems models (OMG-Certified Systems Modeling Professional certification or demonstrated commensurate level of knowledge)
* Experience working in an Agile development environment
* Familiarity with DoD and/or IC Belong, Connect and Grow at KBR At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team's philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver - Together. KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.

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About KBR

Sourced by ZipRecruiter

At KBR, we partner with government and industry clients to provide purposeful and comprehensive solutions with an emphasis on efficiency and safety. With a full portfolio of services, proprietary technologies and expertise, our employees are ready to handle projects and missions from planning and design to sustainability and maintenance. Whether at the bottom of the ocean or in outer space, our clients trust us to deliver the impossible on a daily basis.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Houston, TX, US

Year founded

1998