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Hourly Embedded Machine Learning Jobs in Michigan

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ...

Aptiv

Embedded Systems Architect

Troy, MI · On-site

$164K/yr

In this role, you will contribute to the architecture, implementation, and deployment of embedded platforms spanning sensor integration, edge computing, autonomy, and machine learning-based ...

dsm-firmenich

$100K - $140K/yr

Scientist Machine Learning for Ingredient Discovery Location: Princeton, NJ or Long Island City, NY ... The salary or hourly wage scale provided reflects the pay range dsm-firmenich expects to pay the ...

New

Aptiv

Embedded Engineering Manager

Troy, MI

In this role, you will define and execute technology and product roadmaps spanning embedded systems, software platforms, autonomy, and machine learning-based perception, while building and leading ...

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Hourly Embedded Machine Learning information

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are popular job titles related to Hourly Embedded Machine Learning jobs in Michigan?

For Hourly Embedded Machine Learning jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Hourly Embedded Machine Learning jobs in Michigan look for?

The top searched job categories for Hourly Embedded Machine Learning jobs in Michigan are:

What cities in Michigan are hiring for Hourly Embedded Machine Learning jobs?

Cities in Michigan with the most Hourly Embedded Machine Learning job openings:

Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Software Research - AI and Machine Learning

Saint Clair Shores, MI • On-site

Ruri Software Technologies LLC
Software Development • 11 - 50 employees
Learn more about Ruri Software Technologies LLCexternal

$185K/yr

Full-time

Re-posted 24 days ago

Job description

Job Title :Software Research - AI and Machine Learning
Location: Fully Onsite. Warren, MI
Job Description:
This project will investigate methods for efficiently using AI and Machine Learning architecture on embedded computing platforms, optimizing their performance within the constraints of these resource-limited systems.
What you need for this position:
• MS or PHD in Computer Science, Computer Engineering, Software Engineering, or similar.
• Expertise with Android Automotive OS, AOSP, Google Automotive Services SDSK, Kotlin, Java and basic C++
• Expertise in Machine Learning ML / Large Language Models LLM
• Expertise with Embedded Systems Architecture and Design
• Gather feedback for future refinements and potential enhancements.
Years of Experience: 7.00 Years of Experience
Regards
Surya
Surya@rurisoft.com

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