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Mlops Engineer Jobs in Utah (NOW HIRING)

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes. * Optimize compute and storage systems to achieve maximum ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes. * Optimize compute and storage systems to achieve maximum ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes. * Optimize compute and storage systems to achieve maximum ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Job Type: Permanent Full Time Location: Salt Lake City, Utah, United States How ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Job Type: Permanent Full Time Location: Salt Lake City, Utah, United States How ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Job Type: Permanent Full Time Location: Salt Lake City, Utah, United States How ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

Crew Career Center

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

... Engineer with a passion for building robust, efficient, and domain-specific AI systems using ... MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud ...

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

... Engineer with a passion for building robust, efficient, and domain-specific AI systems using ... MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

... Engineer with a passion for building robust, efficient, and domain-specific AI systems using ... MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Location: Salt Lake City, Utah, United States Contract to hire role Description ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Location: Salt Lake City, Utah, United States Contract to hire role Description ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Location: Salt Lake City, Utah, United States Contract to hire role Description ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

System One

AI Engineer

Salt Lake City, UT · On-site

Junior AI Engineer Location: Salt Lake City, Utah, United States Contract to hire role Description ... databases o MLOps practices • Experience with Docker, Kubernetes, and CI/CD pipelines • ...

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All JobsMlops Engineer JobsMlops Engineer Jobs in Utah

Mlops Engineer information

See Utah salary details

$90.7K

$142.3K

$165.1K

How much do mlops engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for mlops engineer in Utah is $142,306.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,687.00 and $153,379.00 per year, depending on experience, location, and employer.

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

What is an MLOps Engineer job?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in machine learning deployment, cloud platforms, and automation tools can earn $300,000 or more annually. High compensation is often associated with specialized expertise, leadership roles, and working in competitive tech environments.

What engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, and MLOps engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. Compensation often includes base salary, bonuses, and stock options, particularly in high-growth tech companies.

What are some common challenges Mlops Engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive in the Mlops Engineer position, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
What are the most commonly searched types of Mlops Engineer jobs in Utah? The most popular types of Mlops Engineer jobs in Utah are:
What are popular job titles related to Mlops Engineer jobs in Utah? For Mlops Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Mlops Engineer jobs in Utah look for? The top searched job categories for Mlops Engineer jobs in Utah are:
What cities in Utah are hiring for Mlops Engineer jobs? Cities in Utah with the most Mlops Engineer job openings:
Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Utah as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $142,306 per year, or $68.4 per hour.
AI Infrastructure Engineer IV

AI Infrastructure Engineer IV

Autonomous Solutions

Mendon, UT • On-site

$93K - $122K/yr

Full-time

Posted 10 days ago

Job description

At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets.
As an AI Infrastructure Engineer IV, you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our compute, storage, and cloud environments are scalable, efficient, and tuned for high-performance AI workloads. Working closely with data scientists, robotics engineers, and software teams, you'll develop robust infrastructure that supports the deployment and reliability of our AI-driven autonomous systems.
Responsibilities:
  • Design, build, and maintain high-performance computing infrastructure including CPUs, GPUs, storage, and networking to support AI and ML workloads.
  • Deploy and manage AI systems within cloud environments (AWS, Azure, GCP), ensuring scalability, cost-efficiency, and high availability.
  • Collaborate with data scientists, ML engineers, and software teams to support AI model development, training, and deployment workflows.
  • Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes.
  • Optimize compute and storage systems to achieve maximum performance and throughput for AI/ML pipelines.
  • Monitor system health and troubleshoot performance bottlenecks, infrastructure issues, and deployment challenges.

Required Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
  • 8+ years of experience in cloud infrastructure, DevOps, or platform engineering with 3+ years working on AI/ML systems.
  • Strong understanding of modern AI infrastructure components, including distributed computing, GPU-accelerated systems, and large-scale storage.
  • Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Proficiency with Kubernetes, Docker, Terraform, or similar containerization and orchestration tools.
  • Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.).
  • Experience implementing CI/CD pipelines, MLOps practices, and automation tooling.

At Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding non-discrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.

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