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Google Cloud Machine Learning Engineer Jobs in Utah

Leash Bio

Machine Learning Engineer

Salt Lake City, UT · On-site

$150K - $200K/yr

Machine Learning Engineer At Leash Biosciences, we are at the cutting edge of integrating machine ... focus on cloud environments (primarily Google Cloud, with flexibility to other platforms)

Tagup Inc

Machine Learning Engineer

Salt Lake City, UT · On-site

$125K - $165K/yr

Machine Learning Engineer Tagup is a defense technology company founded at MIT that is delivering ... Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such ...

Tagup

Machine Learning Engineer

Salt Lake City, UT · On-site

$125K - $165K/yr

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next ... Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such ...

Indeed

Machine Learning Engineer

Salt Lake City, UT · On-site

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98.10K - $134.70K/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

$98.10K - $134.70K/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 ...

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98.10K - $134.70K/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

$98.10K - $134.70K/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 ...

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 ...

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

As of May 28, 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 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 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 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 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 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

Machine Learning Engineer

Leash Bio

Salt Lake City, UT • On-site

$150K - $200K/yr

Other

Medical, Retirement

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Machine Learning Engineer

At Leash Biosciences, we are at the cutting edge of integrating machine learning with drug discovery. Our unique approach focuses on predicting molecular and protein interactions, aiming to revolutionize the field of medicinal chemistry. Our team prides itself on its ability to generate and analyze vast datasets, directly contributing to groundbreaking advancements in drug development.

We offer a supportive and inclusive environment, encouraging personal agency, collaboration, and sharing of knowledge. We're driven by an ambitious goal, and we aim to inspire each other to achieve groundbreaking results. We take big bets and are okay when only some of them pay off.

Benefits include healthcare, 401K match, stock options, free lunches, and access to some of the best outdoor locations in the country.

The Role:

We are seeking a highly skilled and self-driven Machine Learning Engineer to join our team. In this role, you'll be instrumental in handling enormous datasets, orchestrating cloud-based computing resources, and training a multitude of advanced machine-learning models. Your work will directly contribute to our mission of creating foundational models for medicinal chemistry. While you will be dealing with massive amounts of chemical and biological information, biology and chemistry experience is not required. Our dataset can be thought of as billions of labeled sentences so experience with language models is highly relevant.

Key Responsibilities:
  • Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
  • Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
  • Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
  • Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
  • Act as a self-sufficient project manager, overseeing your projects from conception to completion.
About You:
  • Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
  • Comfortable building ML infrastructure
  • Experience working with large amounts of text data, NLP, or training LLMs
  • Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
  • Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred Qualifications:
  • Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
  • Ability to manage own compute cluster
  • Ability to maximize GPU utilization and keep cluster busy 24/7
  • Ability to analyze model results and kick off new experiments in response
  • Experience with BERT or similar language models in PyTorch.
  • Experience or interest in biology, chemistry, or related fields is a plus.

Salary: $150,000 - $200,000 per year

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