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Embedded Machine Learning Engineer Jobs in Utah (NOW HIRING)

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Embedded Software Engineer

Vineyard, UT · On-site

$110K - $165K/yr

The Embedded Software Engineer will be responsible for developing high quality software solutions ... This position includes implementing algorithms and state machines as well as leading small to ...

New

Varsity Tutors

Machine Learning Tutor

Spanish Fork, UT · Remote

$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 ...

Varsity Tutors

Machine Learning Tutor

Cedar City, UT · Remote

$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 ...

Varsity Tutors

Machine Learning Tutor

Provo, UT · Remote

$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 ...

Varsity Tutors

Machine Learning Tutor

Logan, UT · Remote

$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 ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site

$88.50K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences ... Translate scientific and engineering questions into well-defined learning and decision problems ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences ... Translate scientific and engineering questions into well-defined learning and decision problems ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences ... Translate scientific and engineering questions into well-defined learning and decision problems ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98.10K - $134.70K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98.10K - $134.70K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Crew Career Center

Senior ML Engineer

Lehi, UT

$98.10K - $134.70K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Utah

Embedded Machine Learning Engineer information

See Utah salary details

$63.7K

$139.6K

$158.4K

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

As of May 29, 2026, the average yearly pay for embedded machine learning engineer in Utah is $139,636.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,700.00 and $157,500.00 per year, depending on experience, location, and employer.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Utah? For Embedded Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Utah look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Embedded Machine Learning Engineer jobs? Cities in Utah with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Platform Engineer Machine Learning (Utah)

Platform Engineer Machine Learning (Utah)

Waystar

Lehi, UT • On-site

Full-time

Posted 20 days ago

Job description

Job Summary:
Waystar is a company that helps providers simplify healthcare payments and improve financials through innovative technology. They are seeking a Machine Learning Platform Engineer to develop and enhance their machine learning platform, manage model life cycles, and implement data engineering solutions.
Responsibilities:
• Develop and enhance the machine learning platform to manage the full model life cycle
• Build frameworks and tools to enable the data science team developing and enhancing predictive models, support scalable real-time predictions in production
• Design and implement data engineering solutions for model training
• Expand NLP capabilities with advanced analysis techniques to improve text understanding
• Design and implement high-performance, scalable services and applications
• Collaborate with team members to create integrated solutions and ensure timely delivery of quality software and documentation
• Understand and adhere to development standards for consistency across teams
• Perform in-depth technical and performance analyses to troubleshoot production issues
• Monitor and maintain production systems for reliability and efficiency
Qualifications:
Required:
• Bachelor’s degree in Computer Science or related area, Masters preferred
• 7+ years of professional experience writing Python or Java code, with at least 3 years building data platforms
• Expert proficiency with SQL
• NLP
• Seasoned practitioner of engineering best practices such as CI/CD and automated testing
• Comfort working in a Linux environment
• Passion for exploring, applying and following the evolution of cutting edge technologies related to AI, machine learning, NLP and large scale data processing
• Professional experience with MLOps, Docker, Kubernetes, relational databases (PostgreSQL preferred), Kafka, REST API design, and microservices application architectures
• Experience with public cloud solutions, such as AWS or GCP
• Proven track record of successful delivery of progressively complex technical projects
• Coaching and mentoring junior engineers in the team
• Team player DNA with a positive, self-starter attitude
• Attention to detail, highly organized, with an absolute focus on quality of work
Preferred:
• Familiarity with ClearML, Triton, PyTorch, and TensorFlow
• Familiarity with statistics and healthcare domain
• Proven expertise in successful large project/build management and execution
Company:
Waystar is a technology platform that provides healthcare revenue cycle management solutions. Founded in 2017, the company is headquartered in Louisville, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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