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Junior Machine Learning Engineer Jobs in Utah (NOW HIRING)

Leash Bio

Machine Learning Engineer

Salt Lake City, UT

$150K - $200K/yr

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 ...

BILL

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 ... Mentor junior team members and share technical expertise to elevate team capabilities We'd love to ...

BILL

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 ... Mentor junior team members and share technical expertise to elevate team capabilities ...

Pluralsight, LLC

Machine Learning Engineer

Draper, UT · On-site

$121K - $160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$145K - $174K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Mentor junior team members and share technical expertise to elevate team capabilities We'd love to ...

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All JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Utah

Junior Machine Learning Engineer information

See Utah salary details

$30.5K

$65.4K

$99.7K

How much do junior machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for junior machine learning engineer in Utah is $65,364.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,200.00 and $72,800.00 per year, depending on experience, location, and employer.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What engineers make $500,000?

Senior engineers in fields such as software, data engineering, and specialized roles like machine learning engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

How much does a junior ML engineer earn?

A junior machine learning engineer typically earns between $60,000 and $90,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in developing, testing, and deploying machine learning models under the supervision of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, and implementing algorithms using frameworks like TensorFlow or PyTorch. They also help maintain data pipelines and ensure models perform efficiently in production environments. This role is typically entry-level, providing valuable hands-on experience in applying machine learning concepts to real-world problems.

Which 5 jobs will survive AI?

For a Junior Machine Learning Engineer, roles that require complex problem-solving, creativity, and human interaction are more likely to persist alongside AI advancements. These include jobs in healthcare, education, research, specialized technical fields, and management, where human judgment and empathy remain essential. Developing skills in domain expertise, critical thinking, and interdisciplinary knowledge can help ensure long-term employability in an evolving AI landscape.

Can I learn ML in 3 months?

Learning machine learning as a Junior Machine Learning Engineer in three months is possible for individuals with prior programming experience and a strong foundation in mathematics. Focused study on core concepts, practical projects, and familiarity with tools like Python and scikit-learn can help build foundational skills within this timeframe, but mastering advanced topics typically requires longer-term experience. Real-world proficiency often depends on ongoing practice and continuous learning beyond initial training.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Utah? The most popular types of Machine Learning Engineer jobs in Utah are:
What are popular job titles related to Junior Machine Learning Engineer jobs in Utah? For Junior Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Utah look for? The top searched job categories for Junior Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Junior Machine Learning Engineer jobs? Cities in Utah with the most Junior Machine Learning Engineer job openings:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Utah as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $65,364 per year, or $31.4 per hour.

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

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