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Machine Learning Engineer Jobs in Tooele, UT (NOW HIRING)

Pwc

CTIO AI Engineering Manager

Salt Lake City, UT

$73K - $244K/yr

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 ...

Pwc

NGA AI Engineer Manager

Salt Lake City, UT

$73K - $244K/yr

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 ...

Smule

Director of Engineering

Salt Lake City, UT · On-site

Drive Smule's AI-first engineering practices by embedding AI-assisted development, automation, machine learning/deep learning systems, and modern developer productivity tools into daily engineering ...

Teiko

Bioinformatics Engineer

Salt Lake City, UT · On-site

... machine learning. This role is designed for someone interested in working at the intersection of ... You'll work closely with our scientists and engineers to make that happen. More specifically, we're ...

Teiko

Software Engineer

Salt Lake City, UT · On-site

... machine learning. This role is intended for someone interested in working at the intersection of ... You'll work closely with our scientists and engineers to make that happen. More specifically, we're ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Tooele, UT

Machine Learning Engineer information

See Tooele, UT salary details

$29.6K

$120.9K

$181.7K

How much do machine learning engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for machine learning engineer in Tooele, UT is $120,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $145,500.00 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.

More about Machine Learning Engineer jobs

What cities near Tooele, UT are hiring for Machine Learning Engineer jobs?

Cities near Tooele, UT with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Tooele, UT as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $120,895 per year, or $58.1 per hour.

Adjunct Instructor (Artificial Intelligence & Machine Learning)

Salt Lake City, UT • On-site

Neumont College of Computer Science
Colleges, Universities, and Professional Schools • 51 - 200 employees
Learn more about Neumont College of Computer Scienceexternal

Full-time

Re-posted 11 days ago

Job description

As a Neumont University instructor you will develop leadership and mentoring skills that will enhance your career. It can be a very rewarding experience as you see students start to understand complex subjects and gain confidence in their abilities.
Neumont is looking to fill multiple adjunct faculty positions to teach (in-person) in the following area:
  • Artificial Intelligence

Neumont University is looking for tech individuals with in-industry experience to teach the following technologies:
  • Artificial Intelligence :
  • Ability to teach AI fundamentals to complete beginners in clear, accessible terms
  • Familiarity with low-code AI tools, including Microsoft Azure ML Studio
  • AI Data Modeling :
  • Proficiency in SQL/SQLite and relational database design (entity-relationship modeling through normalization)
  • Experience with dimensional modeling / data warehousing (star schemas, OLTP vs. OLAP)
  • Understanding of how data modeling supports ML pipelines (feature stores, vector stores/embeddings, train/serve skew)
  • Ability to teach query optimization, including indexes and reading query execution plans
  • Strong working proficiency in Python, sufficient to review and debug student code live in class
  • Machine Learning Foundations:
  • Comfort teaching and evaluating algorithmic complexity (Big-O: time and space)
  • Solid grounding in core ML concepts: supervised/unsupervised/reinforcement learning, overfitting, neural network fundamentals

Reinforcement Learning :
  • Solid theoretical grounding in reinforcement learning (MDPs, Bellman equations, dynamic programming)
  • Hands-on experience with Monte Carlo methods, TD learning/SARSA, Q-learning, policy gradients, and DQNs
  • Working knowledge of NumPy and PyTorch
  • Ability to teach on-policy vs. off-policy tradeoffs and deep-RL stability concepts (replay buffers, target networks)

QUALIFICATIONS:
  • Bachelor's or higher degree in computer science or a related field AND 4 years of CS related experience (or 8 years of CS related experience without a CS degree)
  • Teaching experience preferred, but not required
  • Ability to work within the U.S. without company sponsorship

LOCATION: In-person, on campus
TIME COMMITMENT:
  • Courses begin October 5, 2026 and are 5 to 10 weeks long, depending on the course.
  • We make classes work around full-time work schedules as we offer AM and PM classes.
  • Adjuncts may spend up to 10 hours a week outside of class doing grading and familiarizing themselves with the curriculum. This time commitment lessens once they get the hang of teaching.

ADVANTAGES TO BEING A NEUMONT FACULTY MEMBER:
  • Improve the lives of students from across the nation through the power of education.
  • Opportunity to give back through educating the next generation of tech experts.
  • Experience the "light" turn on in your student's eyes as you teach and they experience true understanding.
  • Be a part of a computer science institution that focuses on creating software engineers that can DO, not just theorize.
  • Develop your teaching/mentoring skills.

Faculty at Neumont University are responsible for educating students in accordance with the Neumont teaching methodology, which focuses on active learning and engaging students in the learning environment. Faculty members are also responsible for grading and providing valuable feedback to students in a timely manner, mentoring students in groups or individually, evaluating curriculum, adapting coursework and materials as necessary to meet student learning needs, and other activities related to effective instruction.
RESPONSIBILITIES, INCLUDING BUT NOT LIMITED TO:
  • Implement best practices in teaching and project-based learning
  • Submit all new teaching materials to Neumont vault upon completion of each course
  • Work with supervisor to identify areas for personal development and course improvement
  • Utilize feedback from mid-quarter and end-of-quarter evaluations to improve teaching
  • Identify innovative teaching methods to solve curricular problems
  • Teach material defined in the course description and syllabus
  • Maintain and meet the listed student learning goals
  • Utilize the Neumont LMS to keep an updated syllabus, course materials, and grades
  • Provide a safe learning environment for students
  • Answer and deal respectfully with student complaints and problems
  • Use effective assessments that measure student learning
  • Provide timely and accurate feedback to students� assignments, exams, projects, etc.

FAQ
I've never taught before, am I qualified to teach?
We hire industry professionals and help them learn how to be good teachers. Our project-based curriculum means fewer lectures and more hands-on practice. Instructors must have at least 4 years of industry experience and a bachelor's degree in a tech related field. An additional 4 years of outstanding experience and contributions to the field may be substituted for a formal degree.
Do I have to develop the curriculum?
You will use curriculum that has been developed and refined by previous Neumont instructors. We expect that you will share your individual perspective and experiences with the students to supplement the formal curriculum.
Does Neumont offer online courses?
No. Our classes are in-person as it makes for a better teaching/learning experience.
What is the process to get started?
All instructors will go through a formal application process which includes a short teaching demonstration. We will verify your work experience and educational credentials.
NU is an equal opportunity employer and provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Neumont's Annual Security & Fire Safety Report is available online at https://www.neumont.edu/campus-safety under the Student Life section. This report is required by federal law to comply with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and contains policy statements and crime statistics for the school. The policy statements address the school's policies, procedures and programs concerning safety and security. You may also request a paper copy from the Vice President, Student Affairs.

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