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Senior Machine Learning Engineer Jobs in Utah (NOW HIRING)

A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Job Summary As a Machine Learning Engineer II, you will lead the productization of AI/ML research pipelines, transforming proof-of-concept models into robust, scalable, and production-grade systems.

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Senior Machine Learning Engineer information

See Utah salary details

$54.2K

$115.2K

$167.1K

How much do senior machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for senior machine learning engineer in Utah is $115,214.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $130,600.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for 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 Senior Machine Learning Engineer jobs? Cities in Utah with the most Senior Machine Learning Engineer job openings:
Infographic showing various Senior Machine Learning Engineer job openings in Utah as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $115,214 per year, or $55.4 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

University of Utah Health

Salt Lake City, UT • On-site

$101K - $138K/yr

Full-time

Medical, Dental

Re-posted 5 days ago


University Of Utah Health rating

7.7

Company rating: 7.7 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

159th of 880 rated healthcare providers


Job description

Overview
As a patient-focused organization, University of Utah Health exists to enhance the health and well-being of people through patient care, research and education. Success in this mission requires a culture of collaboration, excellence, leadership, and respect. University of Utah Health seeks staff that are committed to the values of compassion, collaboration, innovation, responsibility, integrity, quality and trust that are integral to our mission. EO/AA
Senior Machine Learning Engineers leverage their engineering expertise to solve a variety of technical problems for some of the most challenging and impactful projects in healthcare informatics and machine learning. You will work on a specific project critical to our needs with the opportunity to switch teams and projects as you and our fast-paced business grow. We need machine learning engineers who are versatile, rigorous, display leadership qualities and are enthusiastic to take on new problems. You will design, develop, test, deploy, maintain and enhance machine learning and AI solutions.You will be part of the Innovation Office, a product factory inside the health system of the University of Utah.
Corporate Overview: University of Utah Health is an integrated academic healthcare system with five hospitals including a level 1 trauma center, eleven community health centers, over 1,600 providers, and a health plan serving over 200,000 members. University of Utah Health is nationally ranked and recognized for our academic research, quality standards and overall patient experience. In addition to our clinical delivery system, we have a School of Medicine, School of Dentistry, College of Nursing, College of Pharmacy, and College of Health providing education and training for over 1,250 providers annually. We have over 2 million patient visits annually and research grants exceeding $350 million. University of Utah Hospitals and Clinics represents our clinical operations for the larger health system.
Responsibilities
Essential Functions
  • Creating, managing, maintaining, and refactoring ML codebases, pipelines, and workflows for the innovation office.
  • Collaborating closely with research, medical, and engineering staff to design and implement ML approaches.
  • Implementing scalable ML methods and workflows for high-performance computing (HPC) resources, in close collaboration with research staff and technical staff.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Troubleshooting data analysis issues, including implementation issues, hyper-parameter choices and modeling decision.
  • Assisting in preparation of manuscripts and dissemination of results in the appropriate venues.
  • Conducing tasks independently and communicate optimally to team members and stakeholders.
  • Developing deployable solutions for the health care system.
Knowledge / Skills / Abilities
  • Hands-on coding in C++, Python, PyTorch, or Tensorflow.
  • Foundational understanding of supervised and unsupervised learning, reinforcement learning, and machine learning.
  • Independently execute in the face of ambiguity
  • Leads identifications of dependencies and the development of design documents for a product, application, service, or platform.
  • Write efficient systems code and tests and able to debug distributed systems.
  • Work on-call to monitor systems/product/service for degradation, downtime or interruptions.
  • Innovative mindset with a keen eye for identifying opportunities for improvement.
  • Ability to thrive in a fast-paced, dynamic environment and simultaneously handle multiple projects.
  • Partner effectively with other engineers, product managers, and stakeholders.

Qualifications
Required
  • Bachelor's degree in a relevant field.
  • 5 years of experience in software engineering.

Qualifications (Preferred)
Preferred
  • Experience working in complex academic medical center environments.
  • Experience with large multimodal health datasets.
  • Experience with lifecycle management in a fast-paced software environment.
  • Experience in shipping products and scalable, reliable services.
  • Hands on experience with asynchronous programming and concurrency (threads, tasks, futures, async/await).
  • Experience with Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS), and/or Google Kubernetes Engine (GKE) '
  • Experience in building database engines, query engines, indexing solutions (columnar, full-text, vector), at scale.
  • Experience with programming CUDA, AI systems at scale.
  • Experience with live site operations, Site Reliability Engineering (SRE) or production support roles.
  • Experience in networking, distributed systems, lower-level infrastructure.
  • Experience developing accessible technologies.
  • Proficiency in code and system health, diagnosis and resolution, and software test engineering.
  • Experience with AI agents.
Working Conditions and Physical Demands
Employee must be able to meet the following requirements with or without an accommodation.
  • This is a sedentary position that may exert up to 10 pounds and may lift, carry, push, pull or otherwise move objects. This position involves sitting most of the time and is not exposed to adverse environmental conditions.

Physical Requirements
Listening, Sitting, Speaking, Standing, Walking

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