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Ai Automation Engineer Jobs in Michigan (NOW HIRING)

Stellantis

AI & Automation Engineer

Auburn Hills, MI · On-site

Join our engineering organization as an AI & Automation Engineer focused on building scalable, AI-enabled solutions that streamline the Verification & Validation (V&V) lifecycle. This role develops ...

Stellantis

AI & Automation Engineer

Auburn Hills, MI

Join our engineering organization as an AI & Automation Engineer focused on building scalable, AI-enabled solutions that streamline the Verification & Validation (V&V) lifecycle. This role develops ...

Great Lakes Group

Be Seen First

Automation Engineer

Battle Creek, MI · On-site

$55 - $65/hr

Automation Engineer Location: Marshall, MI Seeking experienced Automation Engineers for a new ... We do not use artificial intelligence (AI) tools to screen, assess, rank, or make hiring decisions.

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All JobsAi Automation Engineer JobsAi Automation Engineer Jobs in Michigan

Ai Automation Engineer information

See Michigan salary details

$32.2K

$93.4K

$142.1K

How much do ai automation engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for ai automation engineer in Michigan is $93,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,400.00 and $107,600.00 per year, depending on experience, location, and employer.

What are AI Automation Engineers?

AI Automation Engineers are professionals who design, develop, and implement artificial intelligence solutions to automate tasks and workflows within organizations. They combine expertise in AI, machine learning, and software engineering to create systems that can perform repetitive or complex tasks efficiently with minimal human intervention. Their work often involves building and integrating AI models, optimizing processes, and ensuring the reliability and scalability of automated solutions. These engineers collaborate closely with data scientists, software developers, and business stakeholders to align automation initiatives with organizational goals.

What is the difference between Ai Automation Engineer vs Data Scientist?

AspectAi Automation EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Engineering, or related field; knowledge of AI, automation toolsBachelor's or higher in Statistics, Computer Science, or related; strong analytical skills
Work EnvironmentTech companies, automation firms, R&D labs; focus on developing AI-driven automation solutionsData analysis teams, research institutions; focus on data modeling and insights
Employer & Industry UsageUsed in manufacturing, software development, AI startupsUsed across finance, healthcare, marketing, and tech sectors
Common Search & Comparison IntentUnderstanding roles in AI automationExploring data analysis careers

While both roles involve working with data and AI, Ai Automation Engineers focus on developing automated AI systems and integrating AI into processes. Data Scientists analyze data to extract insights and build models. The roles overlap in AI knowledge but differ in application and focus areas.

What are some common challenges faced by AI Automation Engineers during project implementation?

AI Automation Engineers often encounter challenges such as integrating new AI models with existing legacy systems, ensuring data quality for accurate model outputs, and managing stakeholder expectations regarding automation outcomes. They must also address issues related to model scalability and robustness, especially when deploying solutions in dynamic production environments. Collaboration with cross-functional teams—including data scientists, software engineers, and business analysts—is essential to navigate these complexities and deliver effective automation solutions.

What are the key skills and qualifications needed to thrive as an AI Automation Engineer, and why are they important?

To thrive as an AI Automation Engineer, you need strong programming skills (such as Python), a solid understanding of machine learning concepts, and typically a degree in computer science, engineering, or a related field. Familiarity with automation frameworks, cloud platforms (like AWS, Azure, or GCP), and machine learning libraries (such as TensorFlow or PyTorch) is often required. Problem-solving ability, adaptability, and effective communication are crucial soft skills for collaborating across teams and addressing complex technical challenges. These skills ensure the successful design, implementation, and scaling of automated AI solutions that drive business efficiency and innovation.
What are popular job titles related to Ai Automation Engineer jobs in Michigan? For Ai Automation Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ai Automation Engineer jobs in Michigan look for? The top searched job categories for Ai Automation Engineer jobs in Michigan are:
What cities in Michigan are hiring for Ai Automation Engineer jobs? Cities in Michigan with the most Ai Automation Engineer job openings:
Ai Automation Engineer jobs near you
Infographic showing various Ai Automation Engineer job openings in Michigan as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $93,371 per year, or $44.9 per hour.
AI & Automation Engineer

AI & Automation Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 10 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

15th of 44 rated automakers

Job description

Join our engineering organization as an AI & Automation Engineer focused on building scalable, AI-enabled solutions that streamline the Verification & Validation (V&V) lifecycle. This role develops automation tools, software applications, and intelligent workflows that increase efficiency, improve quality, and accelerate delivery across engineering teams. You will partner with global stakeholders to design, deploy, and optimize modern automation and AI-driven capabilities.
Key Responsibilities
  • Design and develop software tools, APIs, scripts, and automation workflows supporting Verification & Validation (V&V) engineering activities
  • Build and implement AI-enabled solutions including generative AI use cases for requirements analysis, DVP creation, automated test generation, traceability, and validation evidence review
  • Integrate automation and AI solutions with engineering systems, dashboards, CI/CD pipelines, databases, and validation platforms
  • Develop proof-of-concepts, run pilot programs, gather user feedback, and transition solutions into production environments
  • Collaborate with cross-functional and global teams to define requirements, validate solutions, and drive adoption of automation tools
  • Identify opportunities to reduce manual effort, improve process consistency, and increase engineering efficiency through automation and AI
  • Ensure scalable, maintainable, and well-documented code following software development best practices

Basic Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or a related technical field.
  • Strong programming skills in at least one language such as Python, JavaScript, TypeScript, C#, or C++.
  • 7+ years of relevant experience in this field
  • Experience developing software tools, automation scripts, APIs, data pipelines, or workflow automation solutions.
  • Understanding of software development fundamentals, including version control, debugging, testing, documentation, and maintainable code design.
  • Ability to analyze engineering processes and translate them into structured automation solutions.
  • Strong problem-solving, communication, and collaboration skills.
  • Basic familiarity with AI-enabled tools, generative AI concepts, or AI-assisted software development, with interest in applying AI to engineering automation use cases.

Preferred Qualifications:
  • Experience with AI, machine learning, generative AI, large language models, RAG, vector search, prompt engineering, or AI-assisted software development.
  • Experience developing dashboards, web applications, internal engineering tools, or user-facing automation platforms.
  • Experience with front-end or full-stack development using technologies such as React, TypeScript, or similar frameworks.
  • Familiarity with SQL, relational databases, data modeling, or database-driven application development.
  • Familiarity with cloud platforms, containers, data platforms such as Databricks or similar, and CI/CD tools such as TeamCity, Jenkins, GitHub Actions, Azure DevOps, or similar.
  • Experience working with global teams and supporting adoption of new tools, methods, or automation practices.

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