AI/ML Engineers in AI Validation & Monitoring (AVM) apply data, systems, computer science, clinical workflow, and governance expertise to help ensure that post-deployment monitoring, reporting, and lifecycle evidence for clinical AI products is traceable, decision-ready, and supported by scalable governance technology. They work with AIA Governance Operations, AIA Governance Technologies, clinical and product teams, data and analytics partners, IT, architecture, patient safety, legal and regulatory functions, vendors, and other stakeholders to translate approved AIA Governance Policy, PDM and PDRS requirements, and evidence expectations into practical workflows, specifications, and review outcomes.
As the AI/ML Engineer - Post-Deployment Governance, with the functional assignment of PDRS TRex and Governance Technology Partnership, you will convert approved PDM and PDRS, evidence-lineage, reviewer, and policy requirements into functional requirements for TRex, dashboards, and related governance technology. You will support subject-matter review of PDM and PDRS assessment content when tooling, telemetry, data availability, evidence lineage, reporting workflow, or technology constraints affect governance adequacy; define workflows, evidence objects, required fields, decision states, business rules, traceability, and governance-acceptance criteria; and partner with AIA Governance Technologies on feasibility, backlog refinement, prototypes, user acceptance, release readiness, and defect impact.
- Eliciting and prioritizing requirements from approved policy, PDM and PDRS assessment reviews, recurring evidence and workflow gaps, Product Lead feedback, and post-deployment governance priorities; maintaining a traceable requirements backlog and prioritized roadmap recommendations.
- Translating governance policy and evidence needs into user stories, workflow specifications, data definitions, required fields, decision states, business rules, acceptance scenarios, and functional test cases.
- Defining reusable TRex content models and evidence objects that preserve policy-to-workflow and requirement traceability across metrics, sources, owners, cadence, product and model versions, limitations, actions, and handoffs.
- Developing dashboard and portfolio-reporting requirements that support PDRS status, evidence confidence, conditions, escalation, change and retesting, ownership, next actions, and decision-ready visibility.
- Reviewing PDM and PDRS content and supporting evidence prepared by AIA Governance Operations when tooling, telemetry, data availability, evidence lineage, or reporting workflow is material; documenting required corrections, limitations, and technology or evidence changes.
- Partnering with AIA Governance Technologies on technical feasibility, backlog refinement, prototypes, acceptance criteria, user-acceptance testing, release readiness, and assessment of defects or proposed changes against approved governance requirements.
- Performing governance acceptance of implemented workflows, evidence objects, dashboards, and reporting features; identifying policy-impacting defects, traceability gaps, and release conditions while preserving Governance Technology ownership of technical build and run.
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Converting recurring review findings into scalable TRex patterns, dashboard specifications, vendor expectations, enterprise data needs, templates, and technology priorities, and communicating requirements and findings clearly to technical and non-technical stakeholders.
This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program.
- A master’s degree in engineering, computer science, mathematics, health science, or a related field and 1 year experience, or a bachelor’s degree with 3 years of experience.
- Experience applying AI and machine learning in production environments or similar highly regulated or technology focused industries, showcasing an understanding of healthcare technology.
- Skill in cloud infrastructure environment and software development tools.
- Experience working with large, complex, and heterogeneous data sets, preferably in healthcare.
- Skill in AI/ML techniques and frameworks.
- History of collaborating across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
- Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
- Strong interpersonal, communication, and time management skills.
Preferred Qualifications: - A Ph.D. or other doctorate degree is preferred.
- 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, with the ability to adapt effectively to different project scenarios.
- Ability to articulate complex technical concepts to diverse audiences, facilitating clear understanding and engagement from technical and non-technical stakeholders.
- Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends.
- Experience with healthcare industry informatics standards, best practices, and common data models
- Demonstrated hands-on experience translating AI governance and requirements into TRex workflows, evidence objects, business rules, dashboards, user stories, acceptance criteria, functional tests, and release-readiness assessments.
About Us
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.
- Medical: Multiple plan options.
- Dental: Delta Dental or reimbursement account for flexible coverage.
- Vision: Affordable plan with national network.
- Pre-Tax Savings: HSA and FSAs for eligible expenses.
- Retirement: Competitive retirement package to secure your future.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.
Skills Required
- Master's degree in engineering, computer science, mathematics, health science, or a related field and 1 year of experience, or bachelor's degree with 3 years of experience
- Experience applying AI and machine learning in production environments or regulated or technology-focused industries
- Understanding of healthcare technology
- Skill in cloud infrastructure environments and software development tools
- Experience working with large, complex, and heterogeneous datasets, preferably in healthcare
- Skill in AI/ML techniques and frameworks
- Collaboration across diverse teams and communication of complex technical concepts to non-technical stakeholders
- Familiarity with data engineering, data science, AI Engineering, and MLOps best practices
- Strong interpersonal, communication, and time management skills
- Ph.D. or other doctorate degree
- Knowledge of clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards
- Familiarity with systems or quality engineering practices, regulatory standards, and compliance frameworks
- Experience with healthcare informatics standards, common data models, and industry best practices
- Hands-on experience translating AI governance requirements into TRex workflows, evidence objects, business rules, dashboards, user stories, acceptance criteria, functional tests, and release-readiness assessments
Mayo Clinic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mayo Clinic and has not been reviewed or approved by Mayo Clinic.
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Retirement Support — A no-cost pension plus an employer-matched 403(b)/401(k) is positioned as a standout differentiator, offering strong long-term financial security. Feedback suggests this retirement combination elevates overall total rewards even when base pay is moderate.
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Healthcare Strength — Expanded medical networks, enhanced fertility coverage, and employer absorption of a plan year’s premium increases point to robust healthcare offerings. Feedback suggests annual updates maintain breadth and competitiveness of coverage.
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Parental & Family Support — Adoption assistance, dependent scholarships, child and elder-care resources, and EAP services provide meaningful family-oriented support. Feedback suggests these programs add tangible value beyond salary alone.
Mayo Clinic Insights
What We Do
Mayo Clinic is the first and largest integrated, not-for-profit medical group practice in the world. Doctors from every medical specialty work together to care for patients, joined by common systems and a philosophy of "the needs of the patient come first." More than 3,800 physicians and scientists and 50,900 allied health staff work at Mayo Clinic, which has sites in Rochester, Minn., Jacksonville, Fla., and Scottsdale/Phoenix, Ariz. Mayo Clinic also serves over 70 communities through Mayo Clinic Health System with locations in MN, IA, and WI. Collectively, these locations care for more than 1 million people each year.
