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Embedded Machine Learning Engineer Jobs in Detroit, MI

Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

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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 Jul 9, 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 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 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
Machine Learning Engineering

Machine Learning Engineering

Saanvi Technologies

Dearborn, MI • On-site

Contractor

Re-posted 24 days ago

Job description

Machine Learning Engineer
 
What You’ll Do:
Collaborate with stakeholders to understand ML requirements and develop innovative solutions. 
Build and maintain scalable ML pipelines, infrastructure, and deployment platforms.
Automate model lifecycle processes with CI/CD/CT and MLOps principles.
Work on analytics pipelines supporting predictive modeling, data flows, and APIs.
Ensure data quality, integrity, and compliance across systems.
Skills & Experience:
3+ years developing ML models in production; strong Python programming.
2+ years hands-on with GCP, BigQuery, Cloud Storage, Cloud Run, and Kubernetes.
Experience with CI/CD tools like Tekton, version control (GitHub), and code quality/security tools.
Familiarity with Spark, Airflow, containerization, and cloud platforms (GCP, AWS, Azure).
Bachelor’s degree in Computer Science or related field (Master’s preferred).
Preferred Skills:
Automotive or analytics experience, ML libraries (TensorFlow, PyTorch, Scikit-learn), MLOps platforms.
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About Saanvi Technologies

Sourced by ZipRecruiter

Saanvi Technologies is a staffing company that specializes in providing IT professionals to businesses. Our employees are experts in their field, and have the skills and experience necessary to help businesses grow and succeed. Saanvi Technologies is dedicated to helping businesses achieve their goals, and they have a proven track record of success. Our employees are qualified and reliable, and they always go above and beyond to meet the needs of their customers.

Company size

51 - 200 Employees

Headquarters location

Farmington, MI, US

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