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Machine Learning Engineer Jobs in Utah (NOW HIRING)

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

The Engineer will design, build, and deploy machine learning, generative AI, and agentic AI systems ... Design, build, and optimize machine learning models, including classification, regression ...

AI Engineer

Saint George, UT · On-site

$50K - $90K/yr

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

Extractive Metallurgist

Moab, UT · On-site

$100K - $160K/yr

You'll work closely with operations, engineers, machine learning experts, and data scientists to develop innovative solutions that improve efficiency, recovery, and throughput across our projects.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

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Machine Learning Engineer information

See Utah salary details

$28.7K

$117.2K

$176.2K

How much do machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Utah? The most popular types of Machine Learning Engineer jobs in Utah are:
What are popular job titles related to Machine Learning Engineer jobs in Utah? For Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Machine Learning Engineer jobs? Cities in Utah with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in UT? For Machine Learning Engineer jobs in UT, the most frequently searched job titles are:
Infographic showing various Machine Learning Engineer job openings in Utah as of June 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $117,228 per year, or $56.4 per hour.
Artificial Intelligence (AI) / Machine Learning (ML) Engineers

Artificial Intelligence (AI) / Machine Learning (ML) Engineers

University of Utah

Salt Lake City, UT • On-site

$100K - $135K/yr

Full-time

Retirement

Posted yesterday


University Of Utah rating

7.2

Company rating: 7.2 out of 10

Based on 157 frontline employees who took The Breakroom Quiz

334th of 537 rated colleges and universities


Job description

Announcement
Details
Open Date
05/19/2026
Requisition Number
PRN45104B
Job Title
Artificial Intelligence (AI) / Machine Learning (ML) Engineers
Working Title
AI Engineer
Career Progression Track
P00
Track Level
P4 - Advanced, P3 - Career, P2 - Developing
FLSA Code
Computer Employee
Patient Sensitive Job Code?
No
Standard Hours per Week
40
Full Time or Part Time?
Full Time
Shift
Day
Work Schedule Summary
Monday - Friday 8am-5pm.
VP Area
Academic Affairs
Department
00810 - Scient Comp & Imag Instit-Oper
Location
Campus
City
Salt Lake City, UT
Type of Recruitment
External Posting
Pay Rate Range
100,000-135,000
Close Date
08/19/2026
Priority Review Date (Note - Posting may close at any time)
Job Summary
The AI Engineers Program is a core component of Utah RAISE (Research & AI Infrastructure for a Statewide Ecosystem) and the broader University of Utah AI ecosystem. The program provides applied AI engineering expertise to complement the shared computing infrastructure to enable researchers, educators, and administrators at the U to adopt responsible and scalable AI adoption.
We are hiring a cohort of AI Engineers who can support design, development, and deployment of prototype to production-grade AI solutions for well-scoped and high-impact use cases. This cohort will focus on application-level work: model fine-tuning and adaptation, retrieval-augmented generation pipelines, agentic systems, and production-oriented ML engineering, and will help build durable, in-house capacity to support teaching, research, and innovation across the university.
The AI Engineers Program will be administered by the SCI Institute in coordination with the Office of Artificial Intelligence and the One-U Responsible AI Initiative to serve the broader University of Utah community and beyond.
Responsibilities
  • Accelerate responsible AI integration across teaching and research, helping faculty and students move from ideas to production ready tools and prototypes.
  • Support rapid experimentation, prototyping, and implementation, which is increasingly critical given how quickly AI technologies are evolving.
  • Build and maintain shared tools, frameworks, and pipelines that can be reused across colleges and initiatives, reducing duplication and dependence on external vendors.
  • Help operationalize governance, privacy, and security expectations by embedding them directly into AI solutions.
  • Act as force multipliers, upskilling internal teams and supporting interdisciplinary collaboration.
  • Collaborate with faculty, researchers, and other institutional partners to scope projects and define technical approaches.
  • Provide mentorship and technical guidance to senior undergraduate and MS students in AI technologies and application development.
  • Contribute to open-source software and promote reproducible research practices, helping to foster a culture of transparency and reuse across campus.
  • Design and deliver workshops, training sessions, and educational materials on AI tools and methods.
  • Provide technical consulting to the campus community through structured office hours and project-based engagements.

Minimum Qualifications
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, II: Requires a bachelor's (or equivalency) + 4 years or a master's (or equivalency) + 2 years of directly related work experience.
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, III: Requires a bachelor's (or equivalency) + 6 years or a master's (or equivalency) + 4 years of directly related work experience.
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IV: Requires a bachelor's (or equivalency) + 8 years or a master's (or equivalency) + 6 years of directly related work experience.
Preferences
  • Demonstrated ability to effectively collaborate with researchers and stakeholders across disciplines and levels of technical expertise.
  • Experience in one or more relevant technical domains supporting applied AI development, such as machine learning systems engineering, LLM/GenAI application development, software engineering (e.g., Python, C++, JavaScript), cloud computing, distributed systems, or full-stack development
  • Broad familiarity with AI and research computing and data practices, with the ability to apply sound technical judgment to design, build, and deploy projects with a high degree of independence and creativity.
  • Ability to identify collaboration opportunities and initiatives that would benefit from applied AI integration and partnership with SCI and related programs.
  • Demonstrated experience developing and applying AI/ML techniques (e.g., model training and fine-tuning, large language models, retrieval-augmented generation, or scalable ML systems) in research, scientific, or production-oriented contexts.
  • Professional experience working in technical roles involving complex software-based systems, research computing environments, or data-driven applications, with responsibilities beyond routine execution.
  • Evidence of applying advanced technical concepts independently, including systems design, problem decomposition, and implementation choices, in environments with incomplete or evolving requirements.
  • Demonstrated experience collaborating with non-peer stakeholders (e.g., researchers, faculty, clients, domain experts, or organizational partners) to translate needs or ideas into technical work.
  • Professional experience operating in environments requiring judgment, discretion, and ethical or policy awareness, such as academic, research, healthcare, government, regulated industry, or similarly constrained settings.
  • Prior experience guiding or supporting others' technical work, such as mentoring, advising, leading technical components of projects, or providing consultative support.
  • Demonstrated ability to communicate technical work clearly in written and verbal form to audiences with varying levels of technical expertise.

Type
Benefited Staff
Special Instructions Summary
Additional Information
The University is a participating employer with Utah Retirement Systems ("URS"). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS' post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.
The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.
Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran's status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX (OEO). More information, including the Director/Title IX Coordinator's office address, electronic mail address, and telephone number can be located at the: University of Utah Non-Discrimination page.
Online reports may be submitted at https://oeo.utah.edu
https://publicsafety.utah.edu/safetyreport/ This report includes statistics about criminal offenses, hate crimes, arrests and referrals for disciplinary action, and Violence Against Women Act offenses. They also provide information about safety and security-related services offered by the University of Utah. A paper copy can be obtained by request at the Department of Public Safety located at 1658 East 500 South.
As per University of Utah policy 5-108: Transfer of Benefits Eligible Staff Members, a new hire to the University of Utah who is still serving a 12 month probationary period will not be hired into another University of Utah job (a transfer) until the successful completion of the probationary period.

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About University of Utah

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The University of Utah is the state’s flagship institution of higher education, with 18 schools and colleges, more than 100 undergraduate majors and graduate programs, and an enrollment of more than 38,000 students. It is a member of the Association of American Universities—an invitation-only, prestigious group of 71 leading research institutions. The U is advancing a new national model for higher education that delivers societal impact through education, research, health care, and community service, while making social, economic, and cultural contributions that improve lives across Utah and around the world.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Salt Lake City, UT, US

Year founded

1850