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Embedded Machine Learning Engineer Jobs in Taylorsville, UT

Waystar

Platform Engineer Machine Learning (Utah)

Lehi, UT · On-site

  • Medical

  • Retirement

  • PTO

ABOUT THIS POSITION We are looking for a Machine Learning Platform Engineer - Backend Services that will help us build out the platform that supports the training and application of our predictive ...

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

  • Medical

  • Retirement

  • PTO

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 · On-site

$98K - $134K/yr

  • Medical

  • Retirement

  • PTO

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 ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

  • Medical

  • Retirement

  • PTO

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 ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

  • Medical

  • Retirement

  • PTO

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 ...

Octanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

OC Tanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Pwc

AI Engineer

Salt Lake City, UT · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

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Showing results 21-40

All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Taylorsville, UT

Embedded Machine Learning Engineer information

See Taylorsville, UT salary details

$65.8K

$144.2K

$163.6K

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

As of Aug 19, 2026, the average yearly pay for embedded machine learning engineer in Taylorsville, UT is $144,173.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,600.00 and $162,600.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

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 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 cities near Taylorsville, UT are hiring for Embedded Machine Learning Engineer jobs?

Cities near Taylorsville, UT with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Taylorsville, UT as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $144,173 per year, or $69.3 per hour.

Platform Engineer Machine Learning (Utah)

Waystar

Lehi, UT • On-site

Full-time

Medical, Retirement, PTO

Re-posted 22 days ago

Job description

ABOUT THIS POSITION
We are looking for a Machine Learning Platform Engineer - Backend Services that will help us build out the platform that supports the training and application of our predictive models and performs deep analysis to extract machine consumable meaning from unstructured clinical documentation. You will be joining a small team that has become one of the top players in our field in just two years. Because we work on the cutting edge of a lot of technologies, we need someone who is a creative problem solver, resourceful in getting things done, and productive working independently or collaboratively. You will be accessing our enormous amount of data to help drive our future innovation.
WHAT YOU'LL DO
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

WHAT YOU'LL NEED
  • Minimum Requirements (Education, certifications and experience):
  • 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 Requirements:
  • Familiarity with ClearML, Triton, PyTorch, and TensorFlow

  • Familiarity with statistics and healthcare domain

  • Proven expertise in successful large project/build management and execution

ABOUT WAYSTAR
Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.
Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful, optimistic & fun.
Waystar products have won multiple Best in KLAS® or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book™ surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.com or follow @Waystar on Twitter.
WAYSTAR PERKS
  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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