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Google Cloud Machine Learning Engineer Jobs in Michigan

For example, designing and implementing a cloud-native application architecture using GKE (Google ... Machine Learning model fine-tuning. Familiarity with data engineering concepts and practices.

Machine Learning Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach ... Skills RequiredTechnical Communication, Communications, Google Cloud Platform, TensorFlow, Data ...

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage ...

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... Experience working with cloud platforms (GCP and/or AWS) * Strong understanding of SDLC, version ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Senior Machine Learning Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud ...

Google AI Lead Architect

Detroit, MI · On-site

$54.50 - $74.75/hr

... Cloud Architect). • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve. Preferred : • Google Professional Machine Learning Engineer ...

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an ... Experience building AI solutions on cloud platforms such as GCP and/or AWS. Strong understanding of ...

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Google Cloud Machine Learning Engineer information

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How much do google cloud machine learning engineer jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for google cloud machine learning engineer in Michigan is $54.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.73 and $62.45 per hour, depending on experience, location, and employer.

What are Google Cloud Machine Learning Engineers?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning Engineer, and why are they important?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What is the salary of an aiml engineer in Google?

A Google Cloud Machine Learning Engineer typically earns a salary ranging from $120,000 to $180,000 annually, depending on experience, location, and level within the company. Compensation may also include bonuses, stock options, and benefits, with higher salaries often associated with advanced skills in cloud platforms and machine learning frameworks.

How much do machine learning engineers make at GCP?

Machine learning engineers at Google Cloud Platform (GCP) typically earn between $120,000 and $180,000 annually, depending on experience, location, and level. Salaries can increase with specialized skills in cloud services, data modeling, and certifications like Google Cloud Professional Machine Learning Engineer.

What is the difference between Google Cloud Machine Learning Engineer vs Data Scientist?

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What engineers make $500,000?

Senior engineers in high-demand fields such as software development, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and technical architects often reach this compensation level in large tech companies or through equity and bonuses.

Does Google hire machine learning engineers?

Yes, Google hires machine learning engineers to develop and implement AI and machine learning solutions across various products and services. These roles typically require expertise in programming, data analysis, and familiarity with tools like TensorFlow and Google Cloud Platform.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning Engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.
What are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Michigan? The most popular types of Google Cloud Machine Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Michigan with the most Google Cloud Machine Learning Engineer job openings:
Infographic showing various Google Cloud Machine Learning Engineer job openings in Michigan as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $114,007 per year, or $54.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

HTC Global Services

Dearborn, MI • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 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 (Google Cloud Platform), 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