A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Job Summary
Join our Pharmacy Department team at Michigan Medicine as a Solution Engineer, where you'll bridge the gap between data science innovation and real-world impact. Coordinate with applied data scientists, analysts, and healthcare leaders to operationalize machine learning and data models across hybrid environments. Your expertise in cloud technologies, data integration, observability, and performance optimization will ensure the seamless delivery of data-driven solutions that transform healthcare.
Responsibilities*
The Pharmacy Department at Michigan Medicine is seeking a skilled Solution Engineer 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.
The ideal candidate will blend technical depth, operational acumen, and a passion for harnessing data-driven solutions to transform healthcare.
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.
- Enterprise Integration: Evaluate, integrate, and consolidate solutions across the broader Michigan Medicine IT ecosystem to ensure interoperability and maximize value.
- Solution Validation: Create prototypes or proof of concepts to validate solution designs and ensure their effectiveness before full-scale implementation.
Required Qualifications*
- Education
- Senior Solution Engineer
- 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
- Lead Solution Engineer
- Master's degree in computer science, Information Systems, or a related field OR
- Bachelor's degree in a relevant field with 5+ years of demonstrated experience in solution architecture, cloud technologies, or machine learning operations
- Experience:
- Senior Solution Engineer
- 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.
- Excellent problem-solving, analytical, and troubleshooting skills
- Strong communication and collaboration abilities
- Familiarity with data science and machine learning concepts
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
Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled any time after the minimum posting period has ended.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.
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