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Product Manager Machine Learning Jobs in Michigan

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No ... Putting your model into production using AWS or GCP. Required Qualifications * BS. in Computer ...

AIPGEE, Advance data Migration, API, Data Management Experience Required: * 5+ years of experience ... A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational ...

AIPGEE, Advance data Migration, API, Data Management Experience Required:5+ years of experience in ... A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational ...

AIPGEE, Advance data Migration, API, Data Management Experience Required: * 5+ years of experience ... A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational ...

AIPGEE, Advance data Migration, API, Data Management Experience Required: * 5+ years of experience ... A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational ...

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027. As a Machine Learning Engineer at Mariana, you'll help build and improve the ...

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... Ensure AI solutions are scalable, secure, reliable, and production-ready * Collaborate with ...

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Product Manager Machine Learning information

See Michigan salary details

$44.9K

$138.9K

$171.7K

How much do product manager machine learning jobs pay per year?

As of Jun 26, 2026, the average yearly pay for product manager machine learning in Michigan is $138,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,900.00 and $171,700.00 per year, depending on experience, location, and employer.

How does a Product Manager specializing in Machine Learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What does a Product Manager for Machine Learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

What are the key skills and qualifications needed to thrive as a Product Manager, Machine Learning, and why are they important?

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.
What are popular job titles related to Product Manager Machine Learning jobs in Michigan? For Product Manager Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Product Manager Machine Learning jobs in Michigan look for? The top searched job categories for Product Manager Machine Learning jobs in Michigan are:
Machine Learning Engineer

Machine Learning Engineer

HTC Global Services

Dearborn, MI • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

Job Title
Machine Learning Engineer
Overview / Summary
We are seeking an experienced Machine Learning Engineer to design, implement, and maintain scalable machine learning and analytics pipeline solutions. The ideal candidate will have expertise in machine learning engineering, cloud platforms, DevSecOps practices, and data engineering technologies. This role involves building and optimizing ML infrastructure, deploying production-grade machine learning solutions, and collaborating with cross-functional teams to improve processes and business outcomes.
Key Responsibilities
  • Collaborate with business and technology stakeholders to understand current and future machine learning requirements.
  • Design and develop machine learning models and software algorithms to solve complex business problems in structured and unstructured environments.
  • Design, build, maintain, and optimize scalable machine learning pipelines, architectures, and infrastructure.
  • Apply machine learning techniques in areas such as computer vision, perception, localization, virtual reality, augmented reality, object detection, tracking, classification, and terrain mapping.
  • Deploy machine learning models and algorithms into production environments and conduct simulations for testing and validation.
  • Automate model deployment, training, and retraining using CI/CD/CT methodologies and MLOps practices.
  • Implement model management processes, including versioning and traceability across environments.
  • Develop, build, and maintain machine learning infrastructure, including data pipelines, deployment platforms, and monitoring solutions.
  • Develop and maintain tools and libraries that support machine learning development and deployment.
  • Automate machine learning workflows using DevSecOps principles and practices.
  • Collaborate with development and operations teams to improve system integration and automate ML pipelines.
  • Design, develop, and manage data flows and APIs between systems and applications.
  • Troubleshoot and resolve issues related to system communication, data flow, and data quality.
  • Collaborate with technical and non-technical stakeholders to gather requirements and ensure successful deployment of data solutions.
  • Create and maintain technical documentation for software components.
  • Ensure systems comply with evolving business needs, data governance policies, and security requirements.
  • Implement and maintain high standards of data quality and integrity.
  • Manage deliverables through project management tools.

Required Qualifications
  • Bachelor's degree in Computer Science, Information Systems, or a related field.
  • 3+ years of experience developing and deploying machine learning models in production environments.
  • 3+ years of Python programming experience.
  • 2+ years of hands-on experience with Google Cloud Platform (GCP), including services such as BigQuery, Google Cloud Storage, Cloud Composer, and/or Cloud Run.
  • Experience using version control systems such as GitHub.
  • 2+ years of experience with code quality and security scanning tools such as SonarQube, Cycode, or FOSSA.
  • 3+ years of experience with data engineering technologies such as Kubernetes, Container-as-a-Service (CaaS) platforms, OpenShift, DataProc, Spark (PySpark), or Airflow.
  • Experience with CI/CD tools and practices, including Tekton or Terraform.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with Atlassian tools such as Jira and Confluence.
  • Experience working in Agile environments.

Preferred Qualifications
  • Master's degree in Computer Science, Data Science, Engineering, or a related field.
  • Experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience with MLOps tools and platforms.
  • Experience working in fast-paced environments with multiple priorities.
  • Demonstrated commitment to continuous learning and professional development.
  • Strong problem-solving skills and passion for technical excellence and innovation.

What Makes HTC A Great Place To Build Your Future
HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.
At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.
Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
#LI-Hybrid #LI-SK8