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Embedded Machine Learning Engineer Jobs in Detroit, MI

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Detroit, MI

Embedded Machine Learning Engineer information

See Detroit, MI salary details

$69.3K

$151.8K

$172.3K

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 Detroit, MI is $151,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,200.00 and $171,300.00 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 Detroit, MI?

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

What job categories do people searching Embedded Machine Learning Engineer jobs in Detroit, MI look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Detroit, MI are:

Embedded Machine Learning Engineer jobs near you

Senior Machine Learning Engineer (Computer Vision & AI)

Faurecia

Auburn Hills, MI • On-site

$115K - $152K/yr

Full-time

Re-posted 27 days ago

Faurecia rating

5.9

Company rating: 5.9 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

Forvia, a sustainable mobility technology leader
We pioneer technology for mobility experience that matter to people.
Your mission, roles and responsibilities
Role Summary
As a Senior Machine Learning Engineer, you will play a key role in developing and deploying advanced AI solutions that drive innovation across our automotive products and manufacturing processes. This role is focused on applied machine learning, with an emphasis on computer vision, predictive analytics, and scalable model deployment.
You will partner with cross-functional teams across engineering, manufacturing, and R&D to design, build, and productionize machine learning models that deliver measurable business impact. This is a hands-on role requiring strong technical depth, ownership of model lifecycle, and the ability to operate effectively in a fast-paced, evolving environment.
Key Responsibilities
  • Design, develop, and deploy machine learning models with a focus on computer vision, predictive maintenance, and anomaly detection
  • Build and maintain end-to-end ML pipelines, including data preprocessing, model training, evaluation, and deployment
  • Collaborate with engineering, manufacturing, and business stakeholders to translate real-world problems into scalable AI solutions
  • Optimize model performance and scalability using GPU acceleration and parallel computing frameworks
  • Leverage Python and deep learning frameworks (PyTorch, TensorFlow) to implement production-ready solutions
  • Partner with data and software engineering teams to integrate models into production systems and workflows
  • Contribute to AI innovation initiatives, including exploration of generative AI use cases in design and engineering contexts
  • Ensure best practices in model reproducibility, documentation, and performance monitoring
  • Stay current with advancements in machine learning and apply relevant techniques to improve existing capabilities

Your profile and competencies to succeed
Your Profile & Competencies
  • Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field
  • 5+ years (preferably 7+) of hands-on experience in machine learning or applied AI roles
  • Strong expertise in machine learning and deep learning, with practical experience in computer vision applications
  • Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow
  • Experience building and deploying models in production environments
  • Familiarity with GPU acceleration (CUDA or similar frameworks) and performance optimization techniques
  • Experience with ML pipelines, model lifecycle management, and scalable system design
  • Ability to work effectively in matrixed, cross-functional environments
  • Strong problem-solving and analytical skills, with the ability to translate complex data into actionable insights
  • Effective communicator, able to explain technical concepts to non-technical stakeholders
  • Experience in automotive, manufacturing, or industrial environments is a strong plus
  • Familiarity with cloud platforms (e.g., Azure) and Agile development practices is preferred

What we can do for you
  • At Forvia, you will find an engaging and dynamic environment where you can contribute to the development of sustainable mobility leading technologies.
  • We are the seventh-largest global automotive supplier, employing more than 157,000 people in more than 40 countries which makes a lot of opportunity for career development.
  • We welcome energetic and agile people who can thrive in a fast-changing environment. People who share our strong values. Team players with a collaborative mindset and a passion to deliver high standards for our clients. Lifelong learners. High performers. Globally minded people who aspire to work in a transforming industry, where excellence, speed, and quality count.
  • We cultivate a learning environment, dedicating tools and resources to ensure we remain at the forefront of mobility. Our people enjoy an average of more than 22 hours of online and in-person training within FORVIA University (five campuses around the world)
  • We offer a multicultural environment that values diversity and international collaboration. We believe that diversity is a strength. To create an inclusive culture where all forms of diversity create real value for the company, we have adopted gender diversity targets and inclusion action plans.
  • Achieving CO2 Net Zero as a pioneer of the automotive industry is a priority: In June 2022, Forvia became the first global automotive group to be certified with the new SBTI Net-Zero Standard (the most ambitious standard of SBTi), aligned with the ambition of the 2015 Paris Agreement of limiting global warming to 1.5°C. Three principles guide our action: use less, use better and use longer, with a focus on recyclability and circular economy.

Why join us
FORVIA is an automotive technology group at the heart of smarter and more sustainable mobility. We bring together expertise in electronics, clean mobility, lighting, interiors, seating, and lifecycle solutions to drive change in the automotive industry.
With a history stretching back more than a century, we are the 7th largest global automotive supplier, employing more than 157,000 people in 43 countries. You'll find our technology in around 1 out of 2 vehicles produced anywhere in the world.
In June 2022, we became the 1st global automotive group to be certified with the SBTI Net-Zero Standard. We have committed to reach CO2 Net Zero by no later than 2045.
As technological innovation and the need for sustainability transform the automotive industry, we are ideally positioned to deliver solutions that will enhance the lives of road-users everywhere.

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