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Machine Learning Manager Jobs in Utah (NOW HIRING)

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 ...

Senior Machine Learning Engineer

Draper, UT

$97K - $134K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Collaborate cross-functionally with product managers, engineers, and data scientists to translate ...

Senior Machine Learning Engineer

Draper, UT · On-site

$114K - $151K/yr

As a Senior Machine Learning Engineer, you will design, build, and deploy machine learning ... managers, engineers, and data scientists to translate business requirements into scalable ML ...

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Collaborate cross-functionally with product managers, engineers, and data scientists to translate ...

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Machine Learning Manager information

See Utah salary details

$46.4K

$74.4K

$107.4K

How much do machine learning manager jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning manager in Utah is $74,385.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,100.00 and $84,200.00 per year, depending on experience, location, and employer.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning executive or specialized researcher, often requiring advanced skills, extensive experience, and leadership responsibilities. These roles may involve overseeing AI strategy, managing teams, and working with cutting-edge tools and frameworks, and they are usually found in large tech companies or innovative organizations offering top-tier compensation.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What is a machine learning manager?

A machine learning manager oversees teams developing and deploying machine learning models and algorithms. They coordinate projects, set strategic goals, and ensure technical quality, often requiring knowledge of data science, programming, and project management tools. Their role involves collaboration with data scientists, engineers, and stakeholders to implement AI solutions effectively.

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

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

Is ML a high paying job?

Machine Learning Managers typically earn high salaries due to the specialized skills required, such as expertise in algorithms, data analysis, and programming languages like Python or TensorFlow. Salaries vary based on experience, location, and industry, but overall, it is considered a well-compensated role in the tech field.

Which 3 jobs will survive AI?

Machine Learning Managers will continue to be essential as they oversee AI projects, interpret complex data, and coordinate teams. Roles requiring high-level strategic thinking, creativity, and emotional intelligence—such as healthcare professionals, educators, and skilled tradespeople—are also likely to persist despite AI advancements. These jobs often involve tasks that are difficult for AI to replicate fully.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Utah? The most popular types of Machine Learning jobs in Utah are:
What cities in Utah are hiring for Machine Learning Manager jobs? Cities in Utah with the most Machine Learning Manager job openings:

Machine Learning Engineer

Leash Bio

Salt Lake City, UT

$150K - $200K/yr

Other

Medical, Retirement

Posted 12 days ago


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