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Senior Embedded Machine Learning Jobs in Michigan

Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities * Develop embedded software for signal processing, sensor integration, and data acquisition * Design ...

Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities * Develop embedded software for signal processing, sensor integration, and data acquisition * Design ...

Mentor senior engineers and shape the long-term technical direction across Autonomy. About you: In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the ...

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Senior Embedded Machine Learning information

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are some common challenges faced by Senior Embedded Machine Learning Engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What are the key skills and qualifications needed to thrive as a Senior Embedded Machine Learning Engineer, and why are they important?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What does a Senior Embedded Machine Learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.
What are the most commonly searched types of Embedded Machine Learning jobs in Michigan? The most popular types of Embedded Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Senior Embedded Machine Learning jobs? Cities in Michigan with the most Senior Embedded Machine Learning job openings:
Machine Learning Engineer III

Machine Learning Engineer III

Michigan Technological University

Ann Arbor, MI • On-site

Full-time

Posted 7 days ago


Michigan Technological University rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

131st of 535 rated colleges and universities


Job description

Machine Learning Engineer III
Job No: 26056
Department: Michigan Tech Rsrch Institute(MTRI)
Work Type: Staff - Full Time
Location: Michigan Tech Research Institute (Ann Arbor, MI)
Full Time / Part Time: Full Time
Categories: Computing, Research
Applications Close:
Sub Department: Michigan Tech Research Institute (MTRI)
Michigan Technological University is an R1 technological research university founded in 1885 in Houghton. Our rural campus is situated just miles from Lake Superior in Michigan's scenic Upper Peninsula and is home to nearly 7,500 students from more than 60 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan's flagship technological university offers more than 185 undergraduate and graduate degree programs. Research focus areas include defense, health, energy, automotive, environment, and aerospace.
The area's waters, forests, and snowfall support year-round recreation, including skiing, snowboarding, hiking, biking, and paddling. The University is an integral part of the region, supported by a friendly and welcoming community that takes pride in being a true college town. We embrace our size, climate, sense of adventure, and originality.
Summary
At Michigan Technological University is seeking a Machine Learning Engineer III for our Michigan Tech Research Institute (MTRI) department. At MTRI, we develop advanced technologies that help our nation better understand, sense, and operate within complex natural and human-made environments. Our work spans multidisciplinary research and applied development, advancing ideas from foundational concepts to mission-relevant prototypes.
We are seeking a Senior Machine Learning (ML) Engineer to lead technical efforts in applied ML research and development (R&D).
This role focuses on designing, developing, and evaluating advanced ML algorithms and systems, leading technical execution across research programs, and advancing capabilities from early-stage concepts through prototype demonstration. The successful candidate will serve as a technical leader within projects and contribute to proposal development and research direction.
Candidates for this position may opt to work in either Ann Arbor, MI or Dayton, OH.
Responsibilities and Essential Duties
1. Lead the development and evaluation of ML algorithms, models, and prototype systems
2. Lead design, development, and evaluation of ML models for structured, unstructured, and sensor-derived data
3. Lead technical execution of ML efforts within research programs
4. Translate sponsor needs into technically sound ML approaches within project scope
5. Define experimental design, validation strategies, and performance metrics to assess model performance and robustness
6. Architect ML pipelines for data ingestion, training, validation, and deployment
7. Present technical results to sponsors and contribute to reports, publications, and briefings
8. Develop and evaluate prototype ML systems, including integration with sensing, software, or hardware platforms
9. Advance ML capabilities across TRLs 2-6 through modeling, experimentation, and demonstration
10. Contribute to proposal development and technical direction within research efforts
11. Mentor junior engineers and support development of technical staff
12. Commit to learning about continuous improvement strategies and applying them to everyday work. Actively engage in University continuous improvement initiatives
13. Apply safety-related knowledge, skills, and practices to everyday work.
Required Education, Certifications, Licensures
Master's or PhD in Computer Science, Electrical Engineering, Applied
Mathematics, Physics, or related field
Required Experience
1. Minimum of 6 years of relevant experience in applied ML research or ML system development
2. Experience leading technical tasks or workstreams within ML projects
Desirable Education and/or Experience
1. 8-12 years of experience in a related technical field
2. Experience serving as PI or Technical Lead on funded research projects, including responsibility for scope, execution, and deliverables
3. Experience leading technical proposal efforts (BAAs, SBIR/STTR, RFPs)
4. Experience contributing to research proposal capture strategy
5. Experience contributing to publications or conference presentations
6. Experience coordinating small teams or groups within ML-focused projects
Required Knowledge, Skills, and/or Abilities
1. Ability to obtain a U.S. Department of Defense security clearance, which requires United States citizenship. Obtaining a national security clearance while holding a dual citizenship will not be possible when the foreign country poses a risk to the national security of the United States
2. Strong knowledge of ML frameworks (e.g., PyTorch, TensorFlow) and Python-based development
3. Proficiency in Python and scientific computing libraries
4. Ability to design and execute rigorous experimental methodologies
5. Ability to communicate technical concepts to sponsors and stakeholder
Desirable Knowledge, Skills, and/or Abilities
1. Active government security clearance at Secret-level or higher
2. Knowledge of sensor-integrated ML (e.g., RF, SAR, geospatial, multimodal data)
3. Experience with MLOps and scalable ML infrastructure
4. Ability to deploy ML systems in secure, hybrid, or HPC environments
5. Ability to guide research technical direction across multiple related efforts or capability areas of a program
Work Environment and/or Physical Demands
WORK ENVIRONMENT: The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The noise level in the work environment is usually low to moderate
Required Training and Other Conditions of Employment
Every employee at Michigan Technological University will receive the following 4 required trainings; additional training may be required by the department.
Required University Training:
• Employee Safety Overview
• Anti-Harassment, Discrimination, Retaliation Training
• Annual Data Security Training
• Annual Title IX Training
Additional training will be required by the department on a periodic basis.
Background Check:
Offers of employment are contingent upon and not considered finalized until the required background check has been performed and the results received and assessed.
Full-Time Equivalent (FTE) % (1=100%)
1
FLSA Status
Exempt
Appointment Term
12 months
Shift
Pay Rate/Salary
Salary is commensurate with experience and qualifications
Title of Position Supervisor
Senior Research Engineer
Posting Type
Internal and External
Dependent on Funding
Yes
Additional Information
This position is contingent upon the continued availability of external funding.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
If you require any auxiliary aids, services, or accommodations during Michigan Tech's hiring process please notify the Human Resources office at 906-487-2280 or hr-help@mtu.edu.
Other Conditions of Employment:
Please note that successful applicants are responsible for ensuring their eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of your appointment, and maintain eligibility without sponsorship throughout your appointment.
Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer that provides equal opportunity for all, including protected veterans and individuals with disabilities.
The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. Michigan Tech will provide a paper copy upon request; please contact the Michigan Tech Public Safety.
In compliance with the federal Drug-Free Schools and Communities Act (DFSCA) and its implementing regulations (34 CFR Part 86), Michigan Tech is committed to maintaining a drugfree campus environment and actively promoting the health and safety of its community. Find our notice that outlines the University's policies, legal sanctions, health risks, and available support resources related to the unlawful possession, use, or distribution of illicit drugs and alcohol.
Required Education, Certifications, Licensures* (minimum requirements)
Advertised: 04 May 2026 Eastern Daylight Time
Applications Close:
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