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Mlops Machine Learning Engineer 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 ... Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD ...

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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Mlops Machine Learning Engineer information

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

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

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What job categories do people searching Mlops Machine Learning Engineer jobs in Utah look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Mlops Machine Learning Engineer jobs? Cities in Utah with the most Mlops Machine Learning Engineer job openings:
Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Utah as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Machine Learning Engineer

Machine Learning Engineer

Tagup

Salt Lake City, UT

$125K - $165K/yr

Full-time

Posted 11 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.