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Machine Learning Engineer Opt Jobs in Utah (NOW HIRING)

Tagup

Machine Learning Engineer

Salt Lake City, UT

$125K - $165K/yr

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems. In this role, you'll go beyond building models ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$97.70K - $134.20K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$114.50K - $151K/yr

As a Senior Machine Learning Engineer, you will design, build, and deploy machine learning solutions that enhance BILL's products and directly impact user experiences. Responsibilities : • Design ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$145.70K - $174.80K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity ...

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Machine Learning Engineer Opt information

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Utah? For Machine Learning Engineer Opt jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Utah look for? The top searched job categories for Machine Learning Engineer Opt jobs in Utah are:
What cities in Utah are hiring for Machine Learning Engineer Opt jobs? Cities in Utah with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you
Machine Learning Engineer

Machine Learning Engineer

Tagup

Salt Lake City, UT

$125K - $165K/yr

Full-time

Posted 10 days ago

Job description

Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We’re growing rapidly and are looking for change-makers passionate about delivering innovative technologies to solve the most challenging problems in the world’s highest stakes environments. This is an exciting opportunity to engage in meaningful work that strengthens national security and contributes to the success of U.S. and allied forces. Join us in shaping the future of defense logistics for a safer tomorrow.


We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems. In this role, you’ll go beyond building models — you’ll design, deploy, and scale AI solutions that directly support mission-critical operations.

This is not a typical ML position. You’ll work at the intersection of cutting-edge research and real-world application, creating models and infrastructure that deliver measurable improvements in reliability, efficiency, and performance.

If you’re motivated by solving complex technical challenges and want your work to make a tangible impact on national security and aviation safety, we want to hear from you.
What You’ll Do
  • Develop, train, and optimize ML models for large-scale applications.
  • Build pipelines for data ingestion and model deployment.
  • Work with engineers and subject-matter experts to refine solutions.
  • Conduct testing and validation to ensure reliability.
  • Co-author technical reports on data analysis and model performance.
  • Continuously improve ML infrastructure and workflows.
  • Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.
What We’re Looking For
  • 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow.
  • Proven ability to deploy ML models into production and work with large, complex datasets.
  • Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines.
  • Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible.
  • Familiarity with datastores (MySQL, Postgres, or MongoDB) and prior exposure to aviation, defense, or other safety-critical environments is a plus.
Salary

The estimated salary range for this position is between $125,000 and $165,000 annually. We strive to provide a competitive salary and benefits package that aligns with our employees’ experience and qualifications. Our primary objective is to attract and retain top talent, and we firmly believe in compensating our employees fairly for their invaluable contributions.

As a rapidly expanding technology company, we extend part-ownership to all team members through an Employee Stock Option Plan. Additionally, we offer comprehensive health insurance benefits, access to the company’s 401K plan, and foster a team-oriented work environment with regular company outings!

Why Join Us?

This is your opportunity to move beyond academic experiments and build AI models that make a real difference in defense and industry. At Tagup, you’ll work with a world-class, agile team in a supportive environment that encourages rapid iteration and continuous learning.

Tagup is an equal opportunity employer and individuals seeking employment with us are considered without regard to race, color, religion, national origin, age, sex, marital status, physical or mental disability, veteran status, gender identity, sexual orientation, or any other characteristic protected by law.

Citizenship: Due to the nature of our work with the U.S. Department of Defense, applicants must be authorized to work for any employer in the U.S. We are unable to sponsor visas at this time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.