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Machine Learning Engineer Jobs in Utah (NOW HIRING)

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

  • Medical

  • Retirement

  • PTO

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

  • Medical

  • Retirement

  • PTO

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

  • Medical

  • Retirement

  • PTO

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

  • Medical

  • Retirement

  • PTO

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 ...

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Faculty Lead & Learning Engineer - Sciences

Lehi, UT · On-site

$96K - $126K/yr

  • Medical

  • Dental

  • Vision

  • PTO

About the role The Faculty Lead & Learning Engineer - Sciences is Outsmart's designated faculty member for undergraduate science-owning course design, development, and quality-across biology ...

AI Engineer

Salt Lake City, UT · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Data Scientists

Salt Lake City, UT · On-site

$75K - $105K/yr

  • Retirement

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

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 ...

Showing results 41-60

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 Aug 19, 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.

What is a machine learning engineer?

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 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 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.

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 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 August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $117,228 per year, or $56.4 per hour.

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

University of Utah

Salt Lake City, UT • On-site

$90K - $135K/yr

Full-time

Retirement

Posted 27 days ago


University Of Utah rating

7.2

Company rating: 7.2 out of 10

Based on 159 frontline employees who took The Breakroom Quiz

384th of 619 rated colleges and universities


Job description

Announcement
Details
Open Date
07/23/2026
Requisition Number
PRN45731B
Job Title
Artificial Intelligence (AI) / Machine Learning (ML) Engineers
Working Title
AI Engineer
Career Progression Track
P00
Track Level
P4 - Advanced, P3 - Career
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
Work Schedule
Full-time, 40 hours per week. Monday through Friday from 8:00 am to 5:00 pm.
Work Location & Residency
This position offers a flexible, mostly remote work schedule for candidates who reside along the Wasatch Front. While most duties can be performed remotely, the employee must be available to attend essential meetings and events on campus as needed.
Work Profile
Hybrid Work
A hybrid telework schedule is available for this position, dependent on operational needs and management approval. The arrangement will be established in partnership with the manager and is subject to ongoing departmental needs.
Travel:
This position may require occasional travel.
VP Area
U of U Health - Academics
Department
02228 - Data Coordinating Center
Location
Campus
City
Salt Lake City, UT
Type of Recruitment
External Posting
Pay Rate Range
$90,188 to $135,601
Close Date
10/23/2026
Priority Review Date (Note - Posting may close at any time)
Job Summary
Artificial Intelligence (AI) / Machine Learning (ML) Engineers
The Utah Data Coordinating Center (DCC) is seeking an experienced AI Engineer to design, build, and operate secure, scalable AI-enabled research platforms. This role sits at the intersection of machine learning, cloud infrastructure, and regulated research environments, supporting national and international research programs. You will work closely with research IT leadership, data engineers, security teams, and external partners to operationalize AI workflows while maintaining strong governance, security, and compliance standards. This is a hands-on engineering role for someone who enjoys building real systems, not prototypes that live on slides. This position will report to the Sr. Supervisor, IT.
Essential Functions:
  • Design and deliver end-to-end hybrid data and AI solutions
    Collaborate with data scientists, engineers, and business stakeholders to design, build, test, deploy, and support scalable data pipelines and AI/ML models across hybrid cloud and on-premises environments. Deliver reliable, production-ready solutions aligned with organizational strategy and enterprise architecture standards.
  • Operationalize machine learning systems using modern MLOps practices
    Partner with cross-functional teams to deploy, monitor, and manage ML models through CI/CD pipelines, model versioning, experiment tracking, automated testing, and lifecycle management frameworks. Support both batch and real-time inference workloads while ensuring reliability, scalability, and maintainability.
  • Build and maintain secure, scalable infrastructure across hybrid environments
    Implement containerized and cloud-native solutions using Docker and orchestration platforms (e.g., Kubernetes) to support data and AI workloads. Apply infrastructure-as-code (IaC) and automation practices to enable reproducibility, scalability, and operational efficiency across on-premises and cloud systems.
  • Ensure secure, compliant, and governed data and AI systems
    Collaborate with security and compliance teams to implement role-based access controls, encryption, network security controls, and audit logging across environments. Align architectures with regulatory frameworks (e.g., HIPAA, NIST, FISMA) and enterprise governance standards while promoting responsible AI practices.
  • Translate business requirements into scalable technical architectures
    Engage with stakeholders to understand strategic objectives and convert them into robust data architectures, algorithms, and automation workflows. Promote shared ownership of solutions, ensuring alignment with long-term sustainability, performance expectations, and enterprise standards.
  • Monitor, optimize, and sustain production systems
    Implement monitoring, logging, and alerting frameworks to track data pipeline health, model performance, data drift, system reliability, and cost efficiency. Apply performance tuning, reliability engineering, and continuous improvement practices to maintain operational excellence.
  • Communicate technical designs and analytical insights clearly
    Document system architectures, data flows, AI workflows, and operational procedures. Present complex technical concepts and model outcomes to both technical and non-technical stakeholders in a clear and actionable manner.
  • Advance engineering excellence and innovation
    Stay current with emerging technologies in data engineering, cloud computing, and applied AI. Evaluate and adopt new tools and methodologies that improve automation, scalability, security, and organizational impact while adhering to best practices and architectural standards.

To learn more about the Utah DCC visit http://uofuhealth.org/UtahDCCThis position is not eligible for work visa sponsorship.
The University of Utah offers a comprehensive benefits package. You can learn more about the great benefits of working for the University of Utah at: benefits.utah.edu
The department may choose to hire at any of the below job levels and associated pay rates based on their business need and budget.
Responsibilities
Artificial Intelligence (AI) / Machine Learning (ML) EngineerResearch, design, develop, test, and support artificial intelligence (AI) and machine learning (ML) frameworks and models. Leverage AI/ML techniques to answer business questions, support business strategies, and deliver valuable quantitative insights to improve products. Develop sophisticated algorithms to automate processes and tasks. Collaborate with internal stakeholders to understand business and technical needs. Code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR). Remain up to speed on cutting edge research for AI technology and concepts.
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IIIConsidered highly skilled and proficient in discipline. Conducts complex, important work under minimal supervision and with wide latitude for independent judgment.
Requires a bachelor's (or equivalency) + 6 years or a master's (or equivalency) + 4 years of directly related work experience.
This is a Career-Level position in the General Professional track.
Expected Pay Range: $90,188 to $123,274
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IV
Recognized as subject matter expert and advanced individual contributor professional. Requires specialized skill set. Conducts highly complex work, unsupervised and with extensive latitude for independent judgment.
Requires a bachelor's (or equivalency) + 8 years or a master's (or equivalency) + 6 years of directly related work experience.
This is an Advanced-Level position in the General Professional track.
Expected Pay Range: $99,587 to $135,601
Minimum Qualifications
EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor's degree = 4 years of directly related work experience).
Department may hire employee at one of the following job levels:
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
  • Experience with MLOps platforms or custom ML deployment pipelines
  • Familiarity with vector databases, embeddings, or RAG-based systems
  • Experience supporting clinical research, biomedical data, or sensitive datasets
  • Familiarity with compliance-driven environments (FISMA Moderate/High, HITRUST, etc.)
  • Experience working in academic or research institutions
  • Strong experience with Python and modern ML/AI tooling
  • Hands-on experience with AWS (or comparable cloud platforms)
  • Experience building and operating CI/CD pipelines
  • Proficiency with Docker and container-based workflows
  • Experience supporting data-intensive or research computing environments
  • Strong understanding of security best practices in regulated environments
  • Ability to work independently and communicate clearly with both technical and non-technical stakeholders

Applicants will be screened according to preferences.
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

Sourced by ZipRecruiter

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