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Ml Infrastructure Engineer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

... data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and ... This role requires strong expertise in data engineering best practices and a deep understanding of ...

Stellantis

Cloud Software Engineer

Auburn Hills, MI · On-site

$56.75 - $73.75/hr

... and infrastructure automation. Preferred Qualifications: * Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field * Experience integrating AI/ML ...

EPSoft Technologies

AI engineer

Dearborn, MI · On-site

$89K - $122K/yr

The team you will be working on supports ML Practitioners and Data Scientists in their Mach1ML ... Experience using orchestration tools like Airflow and have knowledge of Infrastructure as code ...

Zobility

Project Manager - AI/ML & Robotics

Troy, MI · On-site

... infrastructure and tooling teams. • Oversee the execution, ensure all timelines stay aligned ... Required : • Strong and proven background in Engineering or Computer Science with a focus on AI ...

Utilidata

Senior Software Engineer, DevOps

Ann Arbor, MI · On-site +1

$160K - $190K/yr

This engineer will build and maintain the systems that keep our platform running, help shape ... ML-adjacent infrastructure * AI workload scheduling using Kubernetes * Knowledge of Apache Spark ...

THOMSON REUTERS

Principal Engineer

Ann Arbor, MI · Hybrid

You will partner closely with the platform/infrastructure team (who own provisioning and LLM-serving architecture), AI/ML engineers, product, and FinOps to make cost a first-class engineering concern ...

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Showing results 21-40

All JobsMl Infrastructure Engineer JobsMl Infrastructure Engineer Jobs in Michigan

Ml Infrastructure Engineer information

See Michigan salary details

$40.5K

$110.8K

$158.6K

How much do ml infrastructure engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for ml infrastructure engineer in Michigan is $110,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $122,900.00 per year, depending on experience, location, and employer.

What is the difference between Ml Infrastructure Engineer vs Data Engineer?

AspectML Infrastructure EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, experience with cloud platforms, scripting, and ML toolsBachelor's/Master's in CS, experience with databases, ETL, and data pipelines
Work EnvironmentFocus on deploying and maintaining ML systems, cloud infrastructure, and automationDesigning and building data pipelines, managing large datasets, and data storage
Employer & Industry UsageTech companies, AI startups, research labsFinance, healthcare, e-commerce, and data-driven industries

The ML Infrastructure Engineer specializes in building and maintaining the infrastructure that supports machine learning models, focusing on deployment, scalability, and automation. In contrast, Data Engineers primarily develop data pipelines and manage large datasets to enable data analysis and business intelligence. Both roles require strong technical skills and often overlap, but their core focus areas differ significantly.

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

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

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

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

What cities in Michigan are hiring for Ml Infrastructure Engineer jobs?

Cities in Michigan with the most Ml Infrastructure Engineer job openings:

Ml Infrastructure Engineer jobs near you
Infographic showing various Ml Infrastructure Engineer job openings in Michigan as of August 2026, with employment types broken down into 89% Full Time, 4% Part Time, 1% Temporary, and 6% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $110,750 per year, or $53.2 per hour.

Machine Learning Engineering Senior Engineer

Megan soft Inc

Dearborn, MI • On-site

$96K - $131K/yr

Contractor

Posted 12 days ago

Job description

Job Title: ML Ops Engineer
Location: Dearborn, MI (Hybrid – 4 Days/Week Onsite)
Duration: 12 Months
 
 
Note Only W2 Only USC,GC,H4EAD,GCEAD
 
Position Overview
We are seeking an experienced ML Ops Engineer to design, build, and optimize scalable machine learning data pipelines on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in MLOps, Data Engineering, DevOps, Cloud Infrastructure, and Machine Learning to support Ford's connected vehicle and AI/Agentic initiatives.
The role involves developing robust batch and streaming data pipelines, implementing enterprise data governance, maintaining cloud infrastructure, optimizing ML solutions, and collaborating with cross-functional teams to deliver high-quality data products.
Key Responsibilities
  • Design, develop, and maintain scalable ML data pipelines on Google Cloud Platform.
  • Build batch and streaming data pipelines for connected vehicle data.
  • Optimize ML solutions for performance, scalability, security, reliability, and cost.
  • Develop and maintain cloud infrastructure using Terraform and CI/CD pipelines.
  • Build and monitor production data pipelines while providing production support.
  • Implement enterprise data governance, data lineage, and data quality standards.
  • Collaborate with data scientists, AI engineers, and business stakeholders.
  • Enhance DevOps capabilities using GitHub, Tekton, Docker, and GitHub Actions.
  • Deliver software using Agile methodologies, Test-Driven Development (TDD), CI/CD, and DevOps best practices.
  • Resolve code quality issues using SonarQube, Checkmarx, FOSSA, and Cycode.
  • Design Microservices and REST APIs for scalable data processing.
  • Support AI Agentic initiatives and connected vehicle analytics.
  • Troubleshoot production issues and ensure SLA compliance.
  • Continuously improve data engineering solutions and cloud infrastructure.
Required Skills
  • Google Cloud Platform (GCP)
  • Machine Learning / MLOps
  • TensorFlow
  • Python
  • Java
  • Spark
  • SQL
  • Artificial Intelligence / AI
  • Data Governance
  • Data Architecture
  • Cloud Architecture
  • Apache Kafka
  • REST APIs
  • Microservices
  • Git / GitHub / GitHub Actions
  • Terraform
  • Tekton
  • Docker
  • Jira
  • Agile Software Development
  • Strong Technical Communication & Collaboration Skills
Preferred Skills
  • Telematics
  • Data Modeling
  • Cloud Infrastructure
  • Data Mining
  • Database Design
  • Troubleshooting & Problem Solving
  • Leadership / Mentoring Experience
Required Experience
  • Master's degree with 4+ years of experience, or Bachelor's degree with 6+ years of relevant experience.
  • 4+ years of Data Engineering and software product development experience.
  • Strong experience with at least three of the following:
    • Python
    • Java
    • Spark
    • Scala
    • SQL
  • 3+ years building cloud-based production data pipelines using:
    • Google BigQuery, Redshift, or Azure Synapse
    • Airflow
    • MySQL, PostgreSQL, or SQL Server
    • Apache Kafka or GCP Pub/Sub
    • Microservices
    • REST APIs
    • Terraform
    • Docker
    • GitHub Actions
    • Tekton
    • Atlassian Jira
Preferred Experience
  • Ph.D. in Computer Science, Software Engineering, Information Systems, or related field.
  • 2+ years of ML Model Development and/or MLOps experience.
  • Experience with cloud architecture and application migrations.
  • GCP Professional Certifications.
  • Experience contributing to open-source projects.
  • Strong analytics and data profiling skills.
  • Experience implementing end-to-end automation across ML pipelines.
  • Excellent communication and stakeholder management skills.
  • Experience mentoring junior engineers.
Education
Required: Bachelor's Degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or related field.
Preferred: Master's Degree or Ph.D.