ZipRecruiter

Log In

1

Machine Learning Engineer Opt Jobs in Herriman, UT

Bespoke Labs

Machine Learning Engineer

Orem, UT · On-site

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 ...

NICE

Senior Machine Learning Engineer

Sandy, UT · Hybrid

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

NICE

Senior Machine Learning Engineer

Sandy, UT · On-site

$113K - $150K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

Ancestry

Machine Learning Engineer, Co-op

Lehi, UT · Remote

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 ...

Varsity Tutors

Machine Learning Tutor

Provo, UT · Remote

$18 - $40/hr

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

next page

Showing results 1-20

All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Herriman, UT

Machine Learning Engineer Opt information

See Herriman, UT salary details

$29.9K

$122.1K

$183.5K

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

As of Jul 29, 2026, the average yearly pay for machine learning engineer opt in Herriman, UT is $122,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $147,000.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Herriman, UT? For Machine Learning Engineer Opt jobs in Herriman, UT, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Herriman, UT look for? The top searched job categories for Machine Learning Engineer Opt jobs in Herriman, UT are:
What cities near Herriman, UT are hiring for Machine Learning Engineer Opt jobs? Cities near Herriman, UT with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

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.

Apply