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Embedded Machine Learning Engineer Jobs in Orem, UT

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/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

$98K - $134K/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 ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/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 ...

Berkadia

Product Manager - AI

Midvale, UT · Hybrid

This role will partner closely with business subject-matter experts, engineering, data, machine learning, and enterprise technology teams to translate business needs into scalable AI product ...

New

Berkadia

Product Manager - AI

Midvale, UT · On-site

This role will partner closely with business subject-matter experts, engineering, data, machine learning, and enterprise technology teams to translate business needs into scalable AI product ...

New

Stackruit Ltd.

Senior AI/ML Engineer

Draper, UT · On-site

$100 - $130/hr

You'll be a Senior AI/ML Engineer, designing and building AI-powered features like chatbots and ... Expertise in AI, machine learning, and natural language processing (NLP). * Strong communication ...

Jobtailor

Data Scientist

Lehi, UT · On-site

$90 - $130/hr

Python Programming * SQL Proficiency * Machine Learning ATS Optimization Keywords Hard Skills * Data Science * Statistical Methods * Model Evaluation * Data Cleaning * Data Transformation * Pattern ...

New

Raytheon

Software Engineer II

Provo, UT

$92K - $126K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Ability to obtain ...

Raytheon

Software Engineer II

Provo, UT

$92K - $126K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Active and ...

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Showing results 21-40

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

Embedded Machine Learning Engineer information

See Orem, UT salary details

$60.9K

$133.3K

$151.3K

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 Orem, UT is $133,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,300.00 and $150,400.00 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 are popular job titles related to Embedded Machine Learning Engineer jobs in Orem, UT?

For Embedded Machine Learning Engineer jobs in Orem, UT, the most frequently searched job titles are:

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

Embedded Machine Learning Engineer jobs near you

Senior ML Engineer

Waystar

Lehi, UT • On-site

$98K - $134K/yr

Other

Medical, Retirement, PTO

Re-posted 10 days ago

Job description

ABOUT THIS POSITION
Job Description 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 Models (LMs) and agentic architectures. As a core member of the team, you will be instrumental in developing the entire ML pipeline, from sophisticated data extraction techniques to fine-tuning specialized LMs and orchestrating their interactions within a multi-agent framework.
This is a unique opportunity to apply state-of-the-art Generative AI and NLP techniques to a real-world, high-impact problem, leveraging the latest research in agentic AI and LMs to deliver economical and powerful solutions.
WHAT YOU'LL DO
    • Data Pipeline & Knowledge Base Construction:

    • Design, implement, and optimize robust pipelines for ingesting, parsing, and extracting structured information from complex documents (leveraging OCR, document layout analysis, Named Entity Recognition (NER), and Relationship Extraction (RE)).

    • Develop rich, nested JSON schemas for representing structured data and ensure scalable storage

    • Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database.

    • Language Model (LM) Development & Fine-tuning:

    • Research, select, and experiment with appropriate open-source Language Models (Large & Small) (e.g., Phi-3, Mistral, Llama, Nemotron-H families) for specialized tasks.

    • Design and execute efficient fine-tuning strategies (e.g., LoRA, QLoRA, full fine-tuning) on curated, domain-specific datasets to achieve precise performance for tasks like coverage determination, code lookups, and policy rule application.

    • Explore and implement knowledge distillation techniques to transfer capabilities from larger models to smaller, more efficient LMs.

    • Agentic System Design & Implementation:

    • Build and maintain the core agentic framework, including the orchestrator that intelligently routes queries and coordinates interactions between various specialized LM tools.

    • Develop and integrate "tools" (specialized LMs and external APIs) that perform atomic medical necessity tasks, ensuring strict behavioral alignment and structured outputs.

    • MLOps & Deployment:

    • Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (Google Cloud Platform) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run.

    • Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), model versioning, and performance monitoring (latency, throughput, accuracy).

    • Continuous Improvement & Research:

    • Establish effective feedback loops from end-user interactions and system logs to identify areas for model improvement.

    • Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.

    • Stay abreast of the latest research in LMs, agentic AI, NLP, and document understanding, applying relevant advancements to our system.

    • Collaboration:

    • Work closely with subject matter experts, product managers, and other engineers to translate complex requirements into technical solutions and evaluate system performance.

    • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.

    • 3+ years of professional experience in Machine Learning Engineering, with a strong focus on NLP.

    • Proven experience with Language Models (LMs), including model selection, fine-tuning, and deployment.

    • Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).

    • Solid understanding and hands-on experience with core NLP techniques and architectures, especially Transformers.

    • Experience with cloud platforms, particularly Google Cloud Platform (Google Cloud Platform), including services like Vertex AI, Cloud Storage, and compute services.

    • Familiarity with MLOps principles and tools for model serving, monitoring, and pipeline automation.

    • Excellent problem-solving skills, attention to detail, and ability to work independently and collaboratively.

    • Active use of artificial intelligence (AI) tools and techniques to enhance performance, drive innovation, and improve decision-making across business functions.

    • Ability to leverage AI tools and platforms to streamline workflows, improve decision-making, and drive innovation.

    • Curiosity and adaptability in exploring emerging AI technologies, with a mindset for continuous learning and experimentation.

WHAT YOU'LL NEED
  • What Will Make You Stand Out (Preferred Qualifications):
    • Hands-on experience building or contributing to agentic AI systems or multi-agent frameworks.

    • Direct experience with document processing technologies such as OCR, layout parsing, Document AI, or custom information extraction from unstructured text.

    • Experience with Vector Databases (e.g., pgvector, Pinecone, Weaviate, Qdrant) and RAG architectures.

    • Exposure to the healthcare domain, particularly understanding medical terminology, CPT/ICD codes, or regulatory documents.

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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