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Embedded Machine Learning Engineer Jobs in Minnesota

Jobtailor

Machine Learning Engineer

Virginia, MN · On-site

$150 - $190/hr

Guide clients in navigating ML algorithms, tools, and frameworks Requirements * 2+ years of experience with artificial intelligence, data science, or machine learning engineering * Experience with ...

Onsights

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and ... g., embedded systems, microcontrollers) • Prior experience supporting U.S. Department of War ...

Tennant Company

Machine Learning Engineer

Golden Valley, MN · Hybrid

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible for utilizing experience in emerging technologies such as Cloud computing, Big Data, Deep Machine ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

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Embedded Machine Learning Engineer information

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.

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

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Cities in Minnesota with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you

Machine Learning Engineer

Minneapolis, MN

Solution Design Group
IT Services • 201 - 500 employees
Learn more about Solution Design Groupexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago

Job description

SDG is a high-performance software community. We are a team of collaborative and creative consultants who build and deliver custom software for some of the most recognizable local and national brands. In this role, you will be asked to leverage your current skills while also learning new ones. Working in over 500 different technologies and continually learning together, you can expect a one-of-a-kind and award-winning work experience. Our team at SDG has exceptional integrity and the desire to create the best possible customer solutions. We are proud to partner with our customers to consistently provide a successful working relationship as a high-performance team. 

We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our customer's products and services. You will be a part of a tight-knit technical community, giving you the opportunity to constantly grow your development amongst top technical talent. You will work closely with a cross-functional team of data scientists, software engineers, and domain experts to drive the development and deployment of machine learning solutions. SDG is looking for a hard worker with a team-oriented mindset, that has at least 3 years of experience and an in-depth understanding of machine learning and cloud data tools. A successful Machine Learning Engineer at SDG is a lifelong learner who is motivated to continually improve their craft and thrives amongst their fellow employee-owners.
SDG's Machine Learning Engineer's have proven experience with the following responsibilities. If you do too, we want to hear from you:
  • Design, implement, and optimize machine learning algorithms and models to address specific business challenges.
  • Collaborate with data engineers to preprocess and transform raw data into a format suitable for machine learning models. Conduct feature engineering to extract relevant information for model training.
  • Train, validate, and fine-tune machine learning models using state-of-the-art techniques. Evaluate model performance and iterate on models to improve accuracy and efficiency.
  • Deploy machine learning models into production environments and integrate them into existing systems. Collaborate with software engineers to ensure seamless integration with our products.
  • Stay abreast of the latest developments in machine learning and related fields. Proactively identify opportunities to enhance existing models and propose new approaches to solve business problems.
Requirements:
  • 3+ years of hands-on, professional machine learning development experience, delivering solutions in a large scale enterprise environment
  • Experience with Public Cloud Providers such as AWS and Microsoft Azure
  • Experience with AWS and/or Azure data tools and services
  • Demonstrated experience using AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot) to increase development velocity, improve code quality, and support complex problem-solving
  • Strong understanding of data processing, data engineering, and data visualization.
  • Experience with SQL and NoSQL databases
  • Proficient in programming languages such as Python and R
  • Familiarity with big data technologies such as Apache Spark
  • Experience with Machine Learning frameworks such as TensorFlow or PyTorch
  • Ability to work effectively in a collaborative, cross-functional team environment. Excellent communication skills and the ability to explain complex concepts to both technical and non-technical stakeholders.
  • Strong analytical and problem-solving skills. Proven ability to tackle complex problems and deliver robust machine learning solutions.
  • Prior consulting or professional services experience is a bonus
  • Education degree or certification in Computer Science, or the equivalent related work experience
 
What's in it for you?
  • Full-time salaried consultant position
  • A true stake in success. SDG is an ESOP - 100% employee owned 
  • Star Tribune Top Workplace winner the last 7 consecutive years
  • National Top Workplace in 2023, 2024 & 2025
  • Engaged teammates who care about quality solutions 
  • Challenging and rewarding work with great customers 
  • Various opportunities to give back to the community 
  • Be amongst some of the best technologists in the industry
  • Dedicated to our core values of superior customer service, exceptional employee experience, and responsible corporate citizenship
  • Opportunities to connect with other SDGer's via internal communities, committees, and events - virtually and in person
SDG is proud to offer an array of benefits for our employees including but not limited to medical, dental, and vision insurance benefits, paid time off, paid holidays, short and long-term disability, life insurance options, a monthly technology reimbursement allowance, 401k, birth and non-birth parent leave, ESOP, trainings and certifications, and company-owned cabins. Fair and equitable compensation is important to us. The salary range for this opportunity is $130,000 - $170,000. The offer may fall outside this range given factors such as skills and experience. The salary range is subject to change and may be modified at any time.
 
 
Applicants must be authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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