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

Taxbit

Agentic AI Engineer

Salt Lake City, UT · Hybrid

$130K - $170K/yr

Opportunity for Impact TaxBit is seeking an Agentic AI Engineer excited by the intersection of AI ... Bachelor's degree in Computer Science, Machine Learning, relevant technical field, or equivalent ...

Fidelity Corp

Senior Data Engineer

Salt Lake City, UT · On-site

$102K - $139K/yr

Programs testable and maintainable software solutions using Object Oriented (OO) Python programming and Machine Learning (ML) libraries, including Pandas, NumPy, Scikit-learn, and TensorFlow.

swirecc

Data Scientist

Draper, UT · On-site

Employ Artificial Intelligence and Machine Learning techniques across all business channels, customer and consumer segments, markets and products. Pursue use cases to analyze and drive revenue, lower ...

swirecc

Data Scientist

Draper, UT · On-site

Employ Artificial Intelligence and Machine Learning techniques across all business channels, customer and consumer segments, markets and products. Pursue use cases to analyze and drive revenue, lower ...

Amat

UX Engineer IV - (E4)

Salt Lake City, UT · Hybrid

$156K - $214K/yr

As a Software Engineer at Applied Materials, you'll dive deep into ground-breaking technologies-like machine learning and AI-to craft novel software solutions that solve our customers' high-value ...

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Taxbit

Agentic AI Engineer

Salt Lake City, UT · On-site

$130K - $170K/yr

Company Founded by CPAs, tax attorneys, and engineers, Taxbit is the leading innovator automating ... Bachelor's degree in Computer Science, Machine Learning, relevant technical field, or equivalent ...

TaxBit

Agentic AI Engineer

Salt Lake City, UT · Hybrid

$130K - $170K/yr

Company Founded by CPAs, tax attorneys, and engineers, Taxbit is the leading innovator automating ... Bachelor's degree in Computer Science, Machine Learning, relevant technical field, or equivalent ...

Brex

Brex Rotational Program

Salt Lake City, UT · On-site

$58K - $66K/yr

Major, minor, or coursework in a field relevant to AI and data, such as Computer Science, Data Science, Statistics, Machine Learning, Information Systems, or other Engineering. * Basic knowledge or ...

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Showing results 1-20

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 Jul 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants 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 AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $120,895 per year, or $58.1 per hour.
Staff AI Engineer

Staff AI Engineer

Strider Technologies, Inc

South Jordan, UT • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago

Job description

Strider Technologies delivers strategic intelligence that helps organizations make faster, more confident decisions in an increasingly complex global environment. Using cutting-edge AI and proprietary methodologies, we transform open-source data into actionable insights that help protect technology, talent, and supply chains from nation-state risks.
We are looking for an exceptionally motivated Staff AI Engineer to join Strider's Context Engineering team. Context Engineering exists to help shape, stage, and prioritize data for consumption by our analysts, customers, and agentic analytical production processes. We are looking for candidates who are comfortable working across our full data processing pipeline and are motivated by solving problems and having mission impact. We want individuals who are excited to use AI to amplify their leverage and are enthusiastic about the evolving practice of software and agentic engineering.
You will:
  • Build and own services and features to support our Context Engineering organization, focusing on hybrid data search capabilities (using ElasticSearch and S3Vectors) at million to billion document scale.
  • Optimize a variety of LLM-based data processing tasks: for example, entity disambiguation, document quality and relevance scoring, text extraction tasks.
  • Design technical solutions and provide feedback on design documents and architectural decisions across the organization.
  • Participate in code reviews and help improve practices for AI-assisted code review.

What you need to be successful:
  • Bachelor's degree in Computer Science, Engineering, or related field
  • 10+ years of experience
  • Track record of setting technical direction and executing beyond the small team level.
  • Demonstrated examples of making architectural/technical bets that paid off, or course-corrected when they didn't.
  • Experience shipping features and solutions that use LLMs in data heavy environments. Experience with frontier model SDKs (OpenAI, Anthropic, etc.), open-source model providers and frameworks, agentic frameworks.
  • Ability to communicate complex technical concepts and engage with senior stakeholders across disciplines (engineering, product, executives).
  • Self-motivated with excellent problem-solving skills and a strong attention to detail.

Nice-to-haves:
  • Strong opinions about best practices for agentic engineering and AI coding tools, and enthusiasm for further developing best practices.
  • Experience mentoring engineers and developing communities of practice within engineering groups.
  • Comfort and competence deploying features into AWS cloud infrastructure.
  • Master's degree or PhD in Computer Science, Engineering, or related field

How We Work
We're a hybrid team that values autonomy, mission impact, and craftsmanship in equal measure. Here's what that looks like in practice:
  • We own our work end-to-end. Engineers here don't just write code - they help shape the problem, design the solution, and care about what happens after it ships. You'll have genuine ownership over meaningful ML systems, not just tickets in a queue.
  • We build with rigor and move with purpose. We believe quality and velocity aren't at odds. We are looking for developers fully leaning into agentic engineering and AI coding tools to increase their velocity as well as their quality.
  • We collaborate openly across disciplines. Our ML engineers work closely with software engineers and product stakeholders. Perspectives from across the org sharpen our thinking - you'll both contribute to and learn from those conversations regularly.
  • We make space to go deep. Novel research and creative exploration are encouraged, not squeezed into the margins. We create time for engineers to dig into hard problems and invest in their craft - whether that's a new modeling approach, a better evaluation framework, or contributing to internal tooling that raises the whole team's ceiling.
  • We trust each other with the hard stuff. You'll be working on problems where the answers aren't obvious. We want people who are comfortable with ambiguity, willing to surface concerns early, and confident enough to push back when something doesn't seem right.

Why join this team:
  • Immediate Mission Impact: Join a small, agile team where your contributions will have a direct, tangible impact on Strider's mission from day one.
  • Data-Rich Environment: Leverage our large, diverse, proprietary datasets to drive innovation and exploration in machine learning and AI.
  • Continuous Learning: Benefit from our commitment to your personal and professional growth, whether it's mastering new technical skills or learning a new language.
  • Culture of Innovation: Be part of a forward-thinking team that values innovative thinking and the continuous improvement of our practices and solutions.

Benefits:
  • Competitive Compensation
  • Company Equity Options
  • Flexible PTO
  • Wellness Reimbursement
  • US Holidays (office closed)
  • Paid Parental Leave
  • Comprehensive Medical, Dental, and Vision Insurance
  • 401(k) Plan

Strider is an equal opportunity employer. We are committed to fostering an inclusive workplace and do not discriminate against employees or applicants based on race, color, religion, gender, national origin, age, disability, genetic information, or any other characteristic protected by applicable law. We comply with all relevant employment laws in the locations where we operate. This commitment applies to all aspects of employment, including recruitment, hiring, promotion, compensation, and professional development.

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