1

Product Manager Machine Learning Jobs in Utah (NOW HIRING)

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

next page

Showing results 1-20

Product Manager Machine Learning information

See Utah salary details

$46.9K

$145.1K

$179.3K

How much do product manager machine learning jobs pay per year?

As of Jul 29, 2026, the average yearly pay for product manager machine learning in Utah is $145,118.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,400.00 and $179,300.00 per year, depending on experience, location, and employer.

What is the AI PM salary?

The salary for a Product Manager specializing in Machine Learning typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, often including bonuses and stock options. Strong knowledge of AI tools and data-driven decision-making are common requirements for this role.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers or AI research directors, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with significant experience and leadership responsibilities.

How does a Product Manager specializing in Machine Learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What does a machine learning product manager do?

A machine learning product manager oversees the development and deployment of AI and machine learning products, coordinating between data scientists, engineers, and stakeholders. They define product requirements, prioritize features, and ensure that machine learning models meet business goals and performance standards, often using tools like data analysis and model monitoring platforms.

What does a Product Manager for Machine Learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

Which 3 jobs will survive AI?

Product Managers in machine learning will continue to be essential as they oversee AI projects, coordinate teams, and ensure alignment with business goals. Roles requiring complex problem-solving, creativity, and human judgment—such as data scientists and AI ethics specialists—are also likely to persist. These jobs demand skills that are difficult for AI to fully replicate, including strategic thinking and interpersonal communication.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

What are the key skills and qualifications needed to thrive as a Product Manager, Machine Learning, and why are they important?

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.
What are popular job titles related to Product Manager Machine Learning jobs in Utah? For Product Manager Machine Learning jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Product Manager Machine Learning jobs? Cities in Utah with the most Product Manager Machine Learning job openings:
Infographic showing various Product Manager Machine Learning job openings in Utah as of July 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $145,118 per year, or $69.8 per hour.

Machine Learning Engineer

Leash Bio

Salt Lake City, UT • On-site

Full-time

Re-posted 22 days ago


Job description

Job Summary:
Leash Biosciences is at the forefront of integrating machine learning with drug discovery, aiming to revolutionize medicinal chemistry. They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new therapies for devastating diseases.
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.
Qualifications:
Required:
• 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:
• 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.
Company:
Leash Bio uses AI and machine learning to innovate drug design and medicinal chemistry. Founded in 2021, the company is headquartered in Salt Lake City, USA, with a team of 2-10 employees. The company is currently Early Stage.