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Google Cloud Machine Learning Engineer Jobs in Utah

Bespoke Labs

Machine Learning Engineer

Logan, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Bespoke Labs

Machine Learning Engineer

Orem, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning ... Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using ...

Crew Career Center

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning ... Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning ... Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using ...

Bespoke Labs

Machine Learning Engineer

Ogden, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

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Google Cloud Machine Learning Engineer information

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How much do google cloud machine learning engineer jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for google cloud machine learning engineer in Utah is $57.25, according to ZipRecruiter salary data. Most workers in this role earn between $48.80 and $65.19 per hour, depending on experience, location, and employer.

What are Google Cloud Machine Learning Engineers?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning Engineer, and why are they important?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

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

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning Engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Utah? For Google Cloud Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Google Cloud Machine Learning Engineer jobs in Utah look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Utah with the most Google Cloud Machine Learning Engineer job openings:
Google Cloud Machine Learning Engineer jobs near you
DevOps & Google Cloud Platform Engineer

DevOps & Google Cloud Platform Engineer

Medici Land Governance

Salt Lake City, UT • On-site, Remote

$52 - $71.25/hr

Other

Medical, Dental, Vision, Life, Retirement

Re-posted 4 days ago

Job description

Job Description: DevOps & Google Cloud Platform Engineers support the Development Teams in Salt Lake City and Ireland and provide technical support for MLG applications deployed for Zambia, Rwanda, and other sites in the future. You will coordinate with architects and developers to design our cloud and on-premise deployments, ensuring that they are stable and secure. You will help train the rest of the engineering team on best practices. You will audit systems and deliverables for standards of security, monitoring, and reliability. You will also assist with internal technical support (e.g., permissions, and services). What You Will Do:Design and deploy with Kubernetes in Google Cloud Manage and monitor our cloud infrastructure Assist and sometimes lead developers to ensure their products are ready for deployment Develop, maintain, and enhance the CI/CD procedures and processes, communicating and training those aspects to stakeholders Coordinate with architects and developers to design our cloud and on-premise deployments, ensuring that they are stable and secure Help train the engineering team on best practices Audit systems and deliverables for standards of security and reliability Assist with internal technical support (e.g., permissions, services) What You Should Have:Bachelor’s Degree in Computer Engineering or another relevant field 3-5 years of relevant experience, with a proven track record of resolving problems Understanding of Docker and its tooling Familiarity with some IAAS tools, (e.g., Puppet, Chef, Terraform, Vagrant) Understanding of Git and CI/CD best practices, preferably Gitlab (or GitHub) Experience deploying solutions into a Cloud provider, ideally Google Cloud (e.g., Kubernetes, SQL, storage) Experience with DNS, CloudFlare, and cloud networking Excellent communication skills, both written and oral, and the ability to communicate technical issues to the Development team Ability to work remotely and autonomously with little oversight Flexibility to accommodate communication across time zones, sometimes including night and weekend calls Fluency in English, both oral and written Passion for our MLG mission and desire to be part of a dynamic, growing companyWhat We Hope You Have:Experience with Python Experience deploying Java or Node services Familiarity with support services tools (e.g., JIRA) Experience with Kustomize and YAML formatting Experience in a startup Experience with blockchains, big data, or machine learning Business experience, preferably in land and property rights, land titling, and land administration systems What We Offer:Flexible work schedulesComprehensive Medical, Dental, and Vision benefitsBasic Term Life & AD&D (company paid)Short/Long Term Disability (company paid)Employee Assistance Program (EAP) (company paid)401(K) Retirement Plan (6% company match)Supplemental & Voluntary PlansCommuter BenefitsFlexible Spending Account (FSA)Health Savings Account (HSA)Legal & Financial ProtectionPet Insurance & Discount Programs*Benefits vary based on position, tenure, location, and employee election
Additional Information: Equal Employment Opportunity:It is our policy to provide equal employment opportunity for all applicants and associates. This policy includes our commitment to ensure that all employment decisions are made without regard to race, color, religion, gender, national origin, disability, pregnancy, veteran status (including Vietnam era veterans), age, sexual orientation, gender identity, or any other non-job-related characteristic protected by law.

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