Director Google Machine Learning Engineer Jobs in Michigan

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.

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