Senior Principal AI/ML Engineer - Research Sovereign AI

Why Mayo Clinic

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.

Benefits Highlights

• 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.

Responsibilities

Position Summary

The Senior Principal AI/ML Engineer  for AI Representation & EMR Vectorization is the senior technical leader and lead scientist responsible for architecting Mayo Clinic’s unified multimodal EMR representation layer. This role defines and builds the scientific substrate used by foundational models, clinical agents, and research applications. The individual serves as a hands-on expert and player-coach, guiding technical strategy while contributing directly to model development, graph construction, and representation science. Over time, this position will build and lead a specialized team. 

Key Responsibilities

Scientific & Technical Leadership

• Design and implement Mayo’s multimodal EMR representation AI architecture, including text, imaging, waveform, structured data, temporal sequences, and multi-visit trajectories.
• Develop graph-based representations and knowledge graphs linking patients, events, attributes, clinical concepts, and embeddings.
• Integrate graph reasoning, vector similarity search, and hybrid vector–graph pipelines for retrieval-augmented models and agentic reasoning.
• Define standards for temporal modeling, drift-aware embeddings, and sequence alignment across encounters.

Hands-On Modeling & Engineering

• Build large-scale embedding pipelines using transformer-based models, contrastive learning, graph neural networks, and hybrid architectures.
• Implement efficient query layers using vector stores and graph databases.
• Develop interpretable embedding diagnostics, attribution tools, and graph-based audits to enable safe clinical use.
• Explore and implement methods for explaining similarity, graph traversals, temporal evolution, and patient-neighborhood reasoning.

Cross-functional Collaboration

• Work with AI researchers on specialty-specific embeddings, representation refinement, and research prototypes.
• Collaborate with clinicians to operationalize clinically meaningful features, phenotypes, and longitudinal concepts.
• Provide scientific input to the Foundational Model Science Program to ensure alignment between representations and model architectures.

Team Leadership

• Serve as founding technical lead of the Reasoning EMR Representation team.
• Mentor junior scientists and engineers; build a future team specializing in representation learning and graph-based reasoning.

Qualifications

Required

• Master’s in Computer Science, Machine Learning, Biomedical Engineering, or related field. 9 years of relevant experience, or a bachelor’s degree with 11 years of relevant experience. 
• Extensive (9+ years) experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an acute understanding of healthcare technology.
• Hands-on expertise with graph databases, and knowledge graph construction.
• Strong experience with transformer-based models, contrastive learning, and temporal modeling.

• Experience designing or deploying vector search systems and hybrid vector–graph reasoning pipelines.

Preferred

• PhD or Master’s in Computer Science, Machine Learning, Biomedical Engineering, or related field.
• 10+ years experience building production ML systems, including multimodal architectures and representation learning.
• Experience with EMR data, healthcare multimodality, or clinical data integration.
• Experience building patient similarity models, temporal embedding systems, or phenotype discovery pipelines.
• Strong background in explainability, causality, or interpretable ML.
• Prior experience in a player–coach or team-lead role.

Exemption Status

Exempt

Compensation Detail

Education, experience and tenure may be considered along with internal equity when job offers are extended.; $175,406-263,099 annually

Benefits Eligible

Yes

Schedule

Full Time

Hours/Pay Period

80

Schedule Details

Monday - Friday regular day hours

Weekend Schedule

none expected

International Assignment

No

Site Description

Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives.  Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.

Equal Opportunity

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.

Recruiter

Jill Squier