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Entry Level Machine Learning Engineer Jobs in Draper, UT

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 ...

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 deploying machine learning solutions that power BILL's next-generation products. This is an opportunity ...

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 solutions that enhance BILL's products and directly impact user experiences. Responsibilities : • Design ...

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 deploying machine learning solutions that power BILL's next-generation products. This is an opportunity ...

As a Machine Learning Engineer Co-Op on the MLE team, you will work on integrating ML models and Generative AI (GenAI) models, enabling ML/LLM-powered applications, and developing AI agents using ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

The Engineer will design, build, and deploy machine learning, generative AI, and agentic AI systems ... Design, build, and optimize machine learning models, including classification, regression ...

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Entry Level Machine Learning Engineer information

See Draper, UT salary details

$28K

$64.8K

$110.3K

How much do entry level machine learning engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for entry level machine learning engineer in Draper, UT is $64,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,100.00 and $73,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Draper, UT? The most popular types of Machine Learning Engineer jobs in Draper, UT are:
What cities near Draper, UT are hiring for Entry Level Machine Learning Engineer jobs? Cities near Draper, UT with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in Draper, UT as of June 2026, with employment types broken down into 11% Internship, 71% Full Time, 12% Part Time, and 6% Temporary. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $64,843 per year, or $31.2 per hour.

Machine Learning Engineer

Leash Bio

Salt Lake City, UT

$150K - $200K/yr

Other

Medical, Retirement

Posted 13 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