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Hourly Embedded Machine Learning Jobs in Michigan

Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms. * Experience integrating AI and ...

Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms. * Experience integrating AI and ...

Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms. * Experience integrating AI and ...

Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms. * Experience integrating AI and ...

New

Machine Technician

Detroit, MI · On-site

$18.50 - $24/hr

... has not wavered and is deeply embedded in its DNA. So, too, is the founding brothers ... learning and continuous improvement. There are no barriers to impede your progress here and no ...

Machine Builder

Holland, MI · On-site

$20 - $25/hr

Location: Full-time, Hourly position onsite in Holland, MI. Standard shop hours are 7am-3:30pm ... learning and skill enhancement * Ensure proper processes are followed and documented appropriately ...

... machine learning (ML), cybersecurity, and advanced edge hardware. This role collaborates across a ... Lead the development and integration of advanced embedded cybersecurity technologies for GE ...

Machine Builder

Holland, MI · On-site

$20 - $25/hr

Location: Full-time, Hourly position onsite in Holland, MI. Standard shop hours are 7am-3:30pm ... learning and skill enhancement * Ensure proper processes are followed and documented appropriately ...

Work in cross-functional Agile teams spanning AI/ML, embedded software, and system integration disciplines. Basic Qualifications: * Bachelor's degree in computer science, Machine Learning, Data ...

Showing results 41-60

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 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 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:

Infographic showing various Hourly Embedded Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Technical Lead- AI Cockpit

Bosch Group

Plymouth, MI • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 12 days ago


Job description

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry.


Let’s grow together, enjoy more, and inspire each other. Work #LikeABosch


 Reinvent yourself: At Bosch, you will evolve.
• Discover new directions: At Bosch, you will find your place.
• Balance your life: At Bosch, your job matches your lifestyle.
• Celebrate success: At Bosch, we celebrate you.
• Be yourself: At Bosch, we value values.
• Shape tomorrow: At Bosch, you change lives.

Job Description

Role Overview

We are seeking a highly skilled Technical Lead / Architect to drive the design, development, and delivery of next-generation AI-powered smart cockpit solutions for Automotive. This role will lead the technical vision and execution of an intelligent, context-aware in-vehicle experience that transforms the cockpit into a proactive, personalized companion for drivers and passengers.

You will work at the intersection of AI, embedded systems, and automotive software, shaping scalable architectures while coordinating cross-functional teams to bring innovative cockpit experiences to production.

Key Responsibilities

  • Define and own the end-to-end architecture for AI-driven smart cockpit systems across hardware, middleware, and application layers
  • Lead design and implementation of AI/ML pipelines, model optimization, deployment, and lifecycle management
  • Architect multi-model/LLM orchestration and on-device model adaptation (fine-tuning, distillation) for edge automotive deployment, including model selection, routing, and inference optimization on GPU/NPU SoCs
  • Architect efficient edge AI execution, optimizing models for CPU/GPU/NPU (quantization, pruning, latency, power)
  • Design hybrid edge–cloud architectures for personalization, continuous learning, and scalable feature delivery
  • Integrate multimodal AI capabilities (voice, vision, sensor fusion) with real-time and safety-critical constraints
  • Establish robust data pipelines, telemetry, and feedback loops, enabling continuous model validation, performance monitoring, and iterative improvement of AI capabilities in production
  • Define the AI evaluation and observability framework, including model quality testing, regression checks, and production monitoring tied to release readiness
  • Drive technical program execution across architecture, AI, and integration workstreams — including planning, dependencies, risk management, milestone tracking, cross-functional coordination, and stakeholder communication — to ensure on-time, high-quality production readiness
Qualifications

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field with 5+ years of experience in AI/ML-driven system development.
  • Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms.
  • Experience integrating AI and Generative AI/LLM-based capabilities into real-time, resource-constrained environments.
  • Strong knowledge of edge AI optimization techniques (quantization, pruning, distillation) and proficiency in Python and C++, along with experience in embedded AI lifecycle management, including OTA updates and fleet telemetry.
  • Hands-on experience with LLM/generative-AI orchestration and model fine-tuning/adaptation in real-time, resource-constrained environments.
  • Strong understanding of cloud platforms architecture and edge–cloud orchestration, and proven ability to lead cross-functional engineering teams.

Preferred Qualifications

  • Knowledge of automotive cockpit systems (voice assistants & personalization)
  • Experience with on-device voice pipelines (ASR/TTS) and inference-serving stacks on various SoC/processors
  • Exposure to user experience design for in-vehicle systems

Key Competencies

  • Strong technical leadership and architectural thinking
  • Ability to balance innovation with production readiness
  • Excellent communication and stakeholder management skills
  • Strategic mindset with hands-on execution capability
  • Passion for shaping the future of AI-defined vehicles

What You'll Work On

  • AI-powered assistants that understand driver intent and context
  • Personalized, self-learning cockpit experiences
  • Seamless integration of infotainment, productivity, and safety features
  • Next-gen human-machine interfaces (voice, gesture, multimodal AI)

Additional Information

All your information will be kept confidential according to EEO guidelines. 

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled. 

BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives 

· FIRST Robotics (For Inspiration and Recognition of Science and Technology) 

· AWIM (A World In Motion) 

Equal Opportunity Employer, including disability / veterans 

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. 

Your well-being matters at Bosch! We offer a competitive compensation and a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. We're investing in your success!

#LI-JM1