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Embedded Machine Learning Engineer Jobs in Orem, UT

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 ...

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 ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

Sr. Data Engineer

Draper, UT

$107K - $128K/yr

Essential Job Duties As a Senior Data Engineer, you will play a key role in designing, building ... Design, build, and operationalize machine learning pipelines for training, validation, deployment ...

Responsibilities : • Works closely with other Data Scientists, Application Engineering, Product Management, and Operational teams in designing, experimenting with, and implementing machine learning ...

Responsibilities : • Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems ...

Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems applied to design ...

Worksclosely withApplication Engineering,ProductManagement, and Operationalteams in designing, experimenting-with,and implementing machine learning and analytical systems applied to design ...

Worksclosely withApplication Engineering,ProductManagement, and Operationalteams in designing, experimenting-with,and implementing machine learning and analytical systems applied to design ...

Establish financial visibility and governance models for AI and machine learning workloads ... Demonstrated ability to influence Engineering teams and drive operational change without direct ...

Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems applied to design ...

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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 Jun 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 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 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 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:
AI Engineer

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago


Job description

RESPONSIBILITIES:
Kforce has a client in Draper, UT that is seeking an AI Engineer who will operate at the intersection of AI engineering and applied data science. The Engineer will design, build, and deploy machine learning, generative AI, and agentic AI systems that power real-world products and decision-making at scale.
Duties:
* Design, build, and optimize machine learning models, including classification, regression, clustering, and recommendation systems
* Develop and productionize LLM-based solutions, including prompt engineering, retrieval-augmented generation (RAG) pipelines, fine-tuning, and multimodal models
* Build and orchestrate agentic AI workflows (LangGraph or similar), including tool usage, decision logic, and long-running agent execution
* Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate software development, testing, and refactoring while maintaining high standards of quality and correctness
* Design and implement modular sub-agents and reusable tools, applying strong software engineering and data science principles across the agent lifecycle (design, build, evaluate, deploy, iterate)
* Apply embeddings and vector search techniques to enable NLP, semantic search, and retrieval use cases
* Process and analyze large-scale datasets using Python (pandas, scikit-learn, PySpark) and SQL
* Implement MLOps best practices, including CI/CD pipelines, model versioning, monitoring, evaluation, and reproducibility
* Evaluate model and LLM performance in production using offline, online, and incremental evaluation strategies
* Translate complex analytical results into clear, actionable insights for both technical and non-technical stakeholders
* Stay current with emerging trends in AI, ML, generative AI, and agentic systems, and apply them pragmatically to business challenges
REQUIREMENTS:
* Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field
* 2+ years of hands-on experience in data science, machine learning engineering, or applied AI within a fast-paced, production-oriented environment
* Advanced proficiency in Python, including experience with pandas, scikit-learn, and PySpark
* Strong SQL skills for large-scale data analysis and feature engineering
* Proven experience building, tuning, and evaluating machine learning models, with a solid understanding of evaluation metrics and tradeoffs
* Experience with vector embeddings, similarity search, and retrieval pipelines
* Practical experience with LLMs, including prompt engineering, API/SDK integration, multimodal models, and fine-tuning approaches
* Hands-on experience with agentic development frameworks (LangGraph preferred or equivalent), including orchestration patterns, sub-agents, and tool integration
* Experience using AI-assisted (-agentic coding-) development tools, with strong engineering judgment around correctness, testing, and maintainability
* Understanding of the agentic software lifecycle, including evaluation, observability, failure modes, and iterative improvement in production environments
* Familiarity with responsible AI principles, including bias, fairness, and governance in deployed systems
* Ability to translate business problems into scalable AI/ML solutions and communicate effectively across technical and non-technical audiences
* Familiarity with model deployment and MLOps practices, including CI/CD, monitoring, and reproducibility
Nice to Have:
* Experience operating and scaling agentic AI systems in production environments
* Background in recommendation systems, optimization, or decision intelligence
* Experience building and delivering AI-powered products (beyond prototyping or research environments)
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.