AI-ML Engineer - Finance-Hybrid
About The Position
The AI-ML Engineer works within Mayo Clinic’s Financial and Accounting Services group, which focuses primarily on time-series analytics and generative AI solutions for finance applications rather than clinical applications. This is a hybrid position requiring the employee to live within 100 miles of a Mayo Clinic campus for on-site work based on business needs. The role develops, integrates, and standardizes software components and contributes across the AI life cycle, from ideation through production. The engineer works with multidisciplinary teams to understand user needs and requirements, translate feedback into design concepts, analyze data, and build AI/ML solutions. Responsibilities also include engineering systems and tools for AI development, maintaining CI/CD pipelines, following quality system procedures, and supporting safe, effective, and compliant technology development. The role may include training healthcare staff on AI tools and technologies.
Requirements
- A master's degree in engineering, computer science, mathematics, health science, or a related field and one year of experience; or a bachelor's degree and three years of experience.
- Experience applying AI and machine learning in production environments or similar highly regulated or technology-focused industries, with an understanding of healthcare technology.
- Skill with cloud infrastructure environments and software development tools.
- Experience working with large, complex, heterogeneous data sets, preferably in healthcare.
- Skill in AI/ML techniques and frameworks.
- Experience collaborating across diverse teams and communicating complex technical concepts to non-technical stakeholders.
- Familiarity with best practices in data engineering, data science, AI engineering, and MLOps.
- Strong interpersonal, communication, and time management skills.
Nice To Haves
- Expertise delivering time-series analytical models and/or agentic solutions in Copilot Studio or Google.
- A Ph.D. or other doctorate degree.
- Expertise in AI/ML techniques and frameworks such as deep learning, natural language processing, and generative AI, with proficiency in tools such as Python, TensorFlow, PyTorch, scikit-learn, or Keras.
- Knowledge of the healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards.
- Familiarity with systems or quality engineering best practices, regulatory standards, and compliance frameworks, and the ability to adapt them to different project scenarios.
- Expertise in user-centered design, human factors engineering, usability testing, and evaluation across AI product development; ability to conduct expert reviews using established usability methods and explain findings clearly.
- Ability to articulate complex technical concepts to diverse audiences and facilitate understanding among technical and non-technical stakeholders.
- Ability to manage varied workloads and multiple project priorities while staying current on healthcare trends.
- Experience with healthcare informatics standards, best practices, and common data models.
Responsibilities
- Design, develop, integrate, and standardize components for AI-driven solutions.
- Collaborate with clinicians, user experience designers, product managers, IT professionals, and other partners to understand user needs, workflows, and requirements and assess feasibility.
- Translate user feedback and requirements into design concepts and usability specifications.
- Interpret and analyze data to inform strategic decisions and communicate complex findings clearly.
- Use machine learning techniques, including deep learning, natural language processing, computer vision, and large language models, to design, develop, and deploy end-to-end AI solutions.
- Participate in engineering systems used to develop and deploy AI solutions.
- Design, test, and maintain tools and CI/CD pipelines to support consistent and automated AI software development and releases.
- Contribute to best practices and standards for AI development and deployment methodologies, tools, and platforms.
- Provide training and education to healthcare staff on AI tools and technologies.
- Develop, maintain, and follow quality system procedures and contribute to verification, non-clinical validation, and risk mitigation.
Benefits
- Multiple medical plan options.
- Dental coverage through Delta Dental or a reimbursement account for flexible coverage.
- Vision plan with a national network.
- Health Savings Account and Flexible Spending Accounts for eligible expenses.
- Competitive retirement package.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
