Senior Solution Architect

1 day ago

Ann Arbor, Michigan, United States University of Michigan Full time
Job Summary

Michigan Medicine is seeking a skilled Solution Architect to orchestrate the seamless operationalization of machine learning models across both on-premises and cloud environments.

You will design and ensure the continued operation of application systems, bridging the gap between data science innovation and real-world impact.

Key Responsibilities
  • Operationalize Machine Learning Models: Design, build and maintain robust CI/CD pipelines for deploying, monitoring, and managing machine learning models in production.
  • Cloud Migration & Operations: Lead the strategic migration of on-premises systems to the cloud, architecting cloud-native solutions while ensuring operational continuity. Manage cloud resources, optimizing for performance, scalability, and cost-efficiency.
  • Hybrid Infrastructure Management: Maintain and optimize existing on-premises Linux virtual machine environments while transitioning workloads to the cloud.
  • Performance & Reliability: Establish comprehensive monitoring, logging, and alerting systems to track the health of deployed models and infrastructure across all environments. Implement proactive measures for high availability and fault tolerance.
  • Data Integration: Collaborate with data teams to design and implement data pipelines that facilitate seamless data flow between systems, ensuring data accessibility for data model and machine learning workflows. Leverage your Python and SQL expertise to facilitate data transformations and integrations.
  • Scalability: Design and implement solutions that can handle increasing data volumes and user demands, ensuring that our systems remain performant and responsive.
  • Security & Compliance: Implement robust security practices in our workflows to protect sensitive data and ensure compliance with healthcare regulations.
  • Collaboration: Work closely with Data Scientists and Data Architects to translate model requirements into scalable, production-ready solutions.
Requirements
  • Education: Master's degree in computer science, Information Systems, or a related field OR Bachelor's degree in a relevant field with 3+ years of demonstrated experience in solution architecture, cloud technologies, or machine learning operations.
  • Experience: 3-5 years of professional experience in a Solution Architect, DevOps Engineer, or similar role. Lead Solution Engineer: 5+ years of professional experience in a Solution Architect, DevOps Engineer, or similar role, with at least 2 years leading technical teams or projects.
  • Leadership Competencies: Demonstrated ability to lead and mentor technical teams. Experience in defining and implementing technical strategies and roadmaps. Track record of successful project delivery in complex environments. Excellent stakeholder management and communication skills.
  • Strong Proficiency in: Cloud platforms (e.g., Azure, AWS, GCP), Azure preferred. Containerization (e.g., Docker, Kubernetes). CI/CD tools (e.g. GitLab CI/CD, GitHub Actions, Jenkins), GitLab CI/CD preferred. Orchestration tools (e.g. Prefect, Airflow, Dagster), Prefect preferred. Linux virtual machine management. Python and SQL for data manipulation and integration. Experience with operationalizing machine learning models, including model deployment, monitoring, and versioning. Knowledge of data pipelines, ETL/ELT processes, and data integration best practices. Familiarity with data build tool (dbt) preferred.
Desired Qualifications
  • Healthcare industry experience. Experience with data visualization and analytics tools. Understanding of healthcare data governance and regulatory compliance. Proficiency in multiple programming languages. Wide familiarity with various data storage technologies and SQL/SQL-like dialects. Experience with metadata management.

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