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Hourly Embedded Machine Learning Jobs in Michigan

Director of Software Engineering

Auburn Hills, MI · On-site

$239K/yr

... embedded systems, mobile apps, cloud infrastructure, Machine Learning engineering capabilities, product ideation and management, and the growth and management of our evolving team to ensure we're ...

Director of Software Engineering

Auburn Hills, MI · On-site

$239K/yr

... embedded systems, mobile apps, cloud infrastructure, Machine Learning engineering capabilities, product ideation and management, and the growth and management of our evolving team to ensure we're ...

ML Engineer, I - App Engine

Ann Arbor, MI · On-site

$153K - $183K/yr

Familiarity with machine learning technologies (e.g. PyTorch) * Experience with Linux Bonus Points * Experience developing SDK's for complex embedded systems, especially those featuring GPUs or ...

As an Artificial Intelligence and Machine Learning Scientist,you'llbe part of a team that is ... Cross-domain fluency: You connect simulation, embedded systems, and data science to deliver ...

As an Artificial Intelligence and Machine Learning Scientist, you'll be part of a team that is ... Cross-domain fluency: You connect simulation, embedded systems, and data science to deliver ...

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Hourly Embedded Machine Learning information

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.

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 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.

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

Engineer I - Software Algorithm

Magna Services

Auburn Hills, MI

Other

Posted 8 days ago


Job description

Job descriptions may display in multiple languages based on your language selection.
What we offer:
At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.
Group Summary:
Transforming mobility. Making automotive technology that is smarter, cleaner, safer and lighter. That's what we're passionate about at Magna Electronics, and we do it by creating world-class Electronic systems. We are a premier supplier for the global automotive industry with full capabilities in design, development, testing and manufacturing of complex Electronic systems. Our name stands for quality, environmental consciousness, and safety. Innovation is what drives us and we drive innovation. Dream big and create the future of mobility at Magna Electronics.
Job Responsibilities:
This role is not eligible for visa sponsorship. Candidates must have current and ongoing authorization to work in the United States.
JOB SUMMARY
The Computer Vision Algorithm Engineer role focused on ADAS perception that turns camera video feeds (image frames) into a clear understanding of the vehicle's surroundings. The work spans concept through serial production: design and simulate algorithms, analyze and replay data, build and test classical and deep learning models, and optimize for real-time execution on production ECUs. Core tasks include object detection, segmentation, tracking, and image enhancement while meeting accuracy, latency, memory, and power targets. A strong background in image processing, machine learning, and mathematics/physics is required, with familiarity in vehicle dynamics considered a plus.
ESSENTIAL JOB FUNCTIONS
  • Develop (design, implement, optimize) conventional image processing algorithms for automotive embedded serial production projects.
  • Design, develop/tune, and optimize deep learning models for ADAS computer vision features (e.g., pruning, quantization) and improve computational performance.
  • Plan and execute experiments to assess deep learning model effectiveness, compare architectures, and validate results through rigorous component/bench testing.
  • Strong knowledge of various camera models; lens distortion correction; homograph and projective transformations mathematical techniques
  • Analyze large datasets to extract insights, refine models, and improve overall performance and robustness.
  • Stay current with deep learning advances and incorporate innovative techniques and research findings into projects.
  • Collaborate with multidisciplinary (requirements, embedded, testing) teams to integrate models into existing systems and ensure seamless operation within the product ecosystem.
  • Document development processes, maintain detailed experiment logs, and present findings clearly to stakeholders.
  • Analyze defects and test results; perform root-cause analysis and implement algorithm improvements to achieve KPIs.
  • Independently deliver intermediate-to-advanced ADAS algorithm design, implementation, and testing.
  • Perform other duties in support of business objectives; maintain regular attendance; follow safe work procedures and PPE requirements; report hazards, injuries, and illnesses promptly; comply with Quality Operating System (QOS) and all safety regulations.
JOB REQUIREMENTS
Education/Experience
  • Master's degree in computer engineering, Software Engineering, Electrical Engineering, Computer Science, or equivalent.
  • Minimum of 3 years of experience in computer vision and image-processing algorithm development using traditional methods and deep learning, with proven expertise in developing and implementing DNN models.
  • Excellent programming skills with C or C++; familiarity with Python with proficiency in deep learning frameworks (TensorFlow, PyTorch, Keras) is advantageous.
  • Strong grasp of machine learning concepts and neural network architectures (CNNs, RNNs, transformers).
  • Experience in image segmentation, object detection, and image data preparation/enhancement (e.g., normalization, augmentation, filtering, noise reduction, contrast adjustment, image restoration).
  • Experience in optimizing models for performance, including techniques such as quantization and distributed training.
  • Strong problem-solving abilities; capable of working independently and collaboratively; effective at communicating complex concepts to technical and non-technical audiences.
  • Experience with responsibilities listed above in the serial development of automotive electronics is preferred.
Technical Knowledge
  • Strong foundations in mathematics and signal/image/video processing; computer vision fundamentals (object detection, tracking, feature extraction) with C/C++.
  • Experience developing AI and Machine Learning Algorithms for embedded devices.
  • Knowledge of automotive product development practices and structured engineering methodologies; development of portable, reusable, modular software for automotive systems.
  • Strong troubleshooting and debugging skills, using structured problem-solving methods (e.g., 8D).
  • Experience with disciplined software development processes (ASPICE or CMMI); configuration management; and project monitoring/control techniques.
Personal Requirements
  • Able to work effectively in a global environment
  • Able to represent technical topics internally and externally
  • Demonstrates self-motivation, tenacity, and determination.
  • Able to work independently with minimal supervision.
  • Comprehensive knowledge of English (speak & write)

PHYSICAL DEMANDS
Normal amount of sitting and standing, average mobility to move around an office and plant environment, able to conduct normal amount of work on a computer.
LIMITATIONS AND DISCLAIMER
The above job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required for the position. Requirements are representative of minimum levels of knowledge, skills and/or abilities. To perform this job successfully, the employee must possess the abilities or aptitudes to perform each duty proficiently.
All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees.
This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position. Employees will be required to follow any other job-related instructions and to perform other job-related duties as requested by their supervisor in compliance with federal and state laws.
Awareness, Unity, Empowerment:
At Magna, we believe that a diverse workforce is critical to our success. That's why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.
AI-Assisted Screening Disclosure
As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.
Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.
If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.
Worker Type:
Regular / Permanent
Group:
Magna Electronics