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Ai Data Engineer Jobs in Michigan (NOW HIRING)

AI Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and ...

Databricks Data Engineer II

Detroit, MI · On-site

$113K - $136K/yr

Join Deloitte's Core AI & Data practice and help organizations modernize data platforms, strengthen ... As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based ...

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

We're ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to ... Lead and manage the AI & Data practice * Manage and steer the allocation of practice resources ...

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

We're ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to ... Lead and manage the AI & Data practice * Manage and steer the allocation of practice resources ...

Data Engineer

Sterling Heights, MI · On-site

$107K - $128K/yr

Design and implement AI-augmented data engineering solutions-including AI agents, automated data quality processes, and intelligent pipeline components-that drive efficiency across Continental's data ...

Design and implement AI-augmented data engineering solutions--including AI agents, automated data quality processes, and intelligent pipeline components--that drive efficiency across Continental ...

Data Engineer

Sterling Heights, MI · On-site

$106K - $128K/yr

Design and implement AI-augmented data engineering solutions-including AI agents, automated data quality processes, and intelligent pipeline components-that drive efficiency across Continental's data ...

Senior Data Engineer

Auburn Hills, MI · On-site

$100K - $136K/yr

About the Role Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering ...

Sr Databricks Data Engineer

Detroit, MI

$113K - $136K/yr

Join Deloitte's AI & Engineering practice and help organizations transform enterprise technology platforms, modernize data environments, and unlock value through innovation. As a Databricks Engineer ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Experience with agentic AI chatbot development and Generative AI / Microsoft Copilot is strongly ... Data engineering exposure: pipelines, transformations, data modeling concepts, and working with ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that ...

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... We\'re looking for a Principal Data Engineer to own the technical direction and execution of our ...

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... We're looking for a Principal Data Engineer to own the technical direction and execution of our ...

Senior Data Engineer

Auburn Hills, MI

$100K - $136K/yr

About the Role Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering ...

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Showing results 1-20

Ai Data Engineer information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do ai data engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for ai data engineer in Michigan is $113,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $119,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Ai Data Engineer position, and why are they important?

To thrive as an AI Data Engineer, you need strong proficiency in programming (Python, SQL), data architecture, and machine learning fundamentals, typically supported by a degree in computer science, engineering, or a related field. Experience with big data tools (Spark, Hadoop), cloud platforms (AWS, Azure, GCP), and certifications like Google Professional Data Engineer are highly valuable. Excellent problem-solving skills, attention to detail, and effective team communication help distinguish top performers in this role. These abilities ensure the development of robust data pipelines and systems that power accurate AI solutions in a collaborative and rapidly-evolving environment.

What does an AI Data Engineer do?

An AI Data Engineer designs, builds, and manages data pipelines and infrastructure to support AI and machine learning models. They collect, process, and store large datasets, ensuring data is clean, structured, and accessible for AI applications. Their role involves working with big data tools, cloud platforms, and databases to optimize performance and scalability. Collaboration with data scientists and software engineers is essential to deploy and maintain AI solutions efficiently.

Which 3 jobs will survive AI?

AI Data Engineers will continue to be in demand as they design, implement, and maintain AI systems, requiring skills in data management, programming, and machine learning. Other roles likely to persist include cybersecurity specialists, who protect systems from evolving threats, and healthcare professionals, especially those involved in patient care and diagnostics, as these fields require human judgment and empathy. These jobs benefit from specialized skills, certifications, and the ability to adapt to technological advancements.

What are some common challenges an AI Data Engineer might face in their daily work?

AI Data Engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality and consistency, and building scalable data pipelines to handle large volumes of information. Working closely with data scientists and software engineers requires strong collaboration and flexibility to adapt to shifting project requirements or algorithms changes. Keeping up with the latest developments in big data and machine learning tech stacks is also crucial. Overcoming these challenges provides a dynamic work environment and offers valuable learning and career growth opportunities.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior AI engineer, machine learning director, or AI research lead, often offering compensation in that range including salary, bonuses, and stock options. These roles usually require advanced skills in machine learning, deep learning, data engineering, and experience with tools like TensorFlow or PyTorch, often combined with leadership responsibilities and a strong track record of innovation.

What does an AI data engineer do?

An AI data engineer designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence and machine learning models. They work with large datasets, ensure data quality, and use tools like SQL, Python, and cloud platforms to enable efficient data processing and model training.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. High compensation is often associated with leadership roles, specialized expertise, or working in high-demand industries like technology or finance.
What are the most commonly searched types of Ai Data Engineer jobs in Michigan? The most popular types of Ai Data Engineer jobs in Michigan are:
What are popular job titles related to Ai Data Engineer jobs in Michigan? For Ai Data Engineer jobs in Michigan, the most frequently searched job titles are:
Infographic showing various Ai Data Engineer job openings in Michigan as of July 2026, with employment types broken down into 73% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution, with an average salary of $113,060 per year, or $54.4 per hour.
AI Data Engineer

AI Data Engineer

IntraEdge

Detroit, MI • On-site

$113K - $136K/yr

Full-time

Posted 18 days ago


Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME

IntraEdge logo

About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

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