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Ml Engineer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

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 ...

Tech Tammina LLC

GCP Engineer

Dearborn, MI · On-site

Work with software and ML engineers/Data Scientist to tackle challenging AIOps and Gen AI problems ... Develop and manage current CI/CD ecosystem and tools * Find ways to automate and continually ...

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

At least 8 years of progressive experience in AI/ML engineering, including a minimum of 3 years deploying traditional ML and Generative AI/LLM solutions into production. * Demonstrated track record ...

KLA

Sr. Software Engineer - AI/ML

Ann Arbor, MI · On-site

$119K - $158K/yr

Minimum of eight (8) years of software engineering, with 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment. * Proficiency in Python, or ...

KLA Corporation

Sr. Software Engineer - AI/ML

Ann Arbor, MI · Hybrid

$119K - $158K/yr

Minimum of eight (8) years of software engineering, with 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment. * Proficiency in Python, or ...

Kla

Sr. Software Engineer - AI/ML

Ann Arbor, MI · Hybrid

$119K - $158K/yr

Minimum of eight (8) years of software engineering, with 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment. * Proficiency in Python, or ...

KLA Corporation

Sr. Software Engineer - AI/ML

Ann Arbor, MI · On-site

$119K - $158K/yr

Minimum of eight (8) years of software engineering, with 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment. * Proficiency in Python, or ...

Orbotech

Sr. Software Engineer - AI/ML

Ann Arbor, MI · Hybrid

$119K - $158K/yr

Minimum of eight (8) years of software engineering, with 3-5 years of experience in AI/ML, with a proven track record of deploying solutions in a production environment. * Proficiency in Python, or ...

KLA-Belgium

Sr. Software Engineer - AI/ML

Ann Arbor, MI · On-site

$129.60 - $220.30/hr

Minimum of eight (8) years of software engineering experience, with 3-5 years in AI/ML and proven track record of deploying solutions in a production environment. * Proficiency in Python or similar ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

Torc Robotics

Senior SOTIF Engineer

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Our team collaborates across safety, systems engineering, product, V&V, mapping, AI-ML, and SW teams to ensure that safety frameworks are met (e.g. FuSa, SOTIF, AI-Safety, etc.), reducing functional ...

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $200K/yr

ML engineers own the features and models built on top of it. The training and monitoring layer is shared ground you design together. Desired Qualifications * 4-8+ years in data engineering or a ...

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Showing results 41-60

All JobsMl Engineer JobsMl Engineer Jobs in Michigan

Ml Engineer information

See Michigan salary details

$28.8K

$77.7K

$123.8K

How much do ml engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for ml engineer in Michigan is $77,732.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $95,000.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.

What are the most commonly searched types of Ml Engineer jobs in Michigan?

The most popular types of Ml Engineer jobs in Michigan are:

What are popular job titles related to Ml Engineer jobs in Michigan?

For Ml Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Ml Engineer jobs in Michigan look for?

The top searched job categories for Ml Engineer jobs in Michigan are:

What cities in Michigan are hiring for Ml Engineer jobs?

Cities in Michigan with the most Ml Engineer job openings:

Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Michigan as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $77,732 per year, or $37.4 per hour.

AI Data Engineer

IntraEdge

Detroit, MI

$113K - $136K/yr

Full-time

Re-posted 15 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
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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

Social media

Instagram

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