AI/ML Engineer - Revenue Cycle… at Mayo Clinic · Remote

Summary: Mayo Clinic is a top-ranked healthcare provider dedicated to patient care and employee well-being. They are seeking an AI/ML Engineer to architect full-stack AI/ML solutions for the Revenue Cycle, focusing on both agentic orchestration and predictive ML solutions. The role involves collaborating with delivery teams, defining AI architectures, and mentoring engineers while ensuring responsible AI practices. Responsibilities: - Architect full-stack AI/ML solutions for Revenue Cycle, spanning agentic orchestration (UiPath Maestro, LLM agents, RPA bots, human-in-the-loop) and predictive ML - Define reference architectures, design patterns, and guardrails for AI use in Revenue Cycle, in partnership with enterprise architecture, security, and data governance - Lead design of high-complexity solutions such as agentic patient portal inbasket management, combining UiPath Maestro, AI agents, RPA bots, and human-in-the-loop oversight - Develop, evaluate, and productionize ML models using Python, modern ML libraries, and Mayo Clinic's approved cloud and data platforms - Partner with delivery leads, app analysts, and business analysts to translate Revenue Cycle opportunities into AI-enabled solutions with measurable ROI - Establish standards for model lifecycle management, monitoring, bias and drift evaluation, and responsible AI practice aligned to Mayo Clinic policy - Evaluate emerging AI capabilities (new LLM models, agentic frameworks, UiPath releases) and guide when and how to adopt them - Mentor AI/ML engineers and developers across the program; contribute to enterprise AI community of practice Required Qualifications: - 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: - Professional experience in AI/ML engineering, solution architecture, or a combined architect/engineer role - Proven experience designing and delivering agentic or LLM-enabled solutions in production environments - Proven experience building and deploying predictive ML models end-to-end, including feature engineering, evaluation, and monitoring - Strong proficiency in Python and modern ML/AI libraries (scikit-learn, PyTorch or TensorFlow, LangChain, LangGraph or equivalent) - Working experience with UiPath (Studio, Orchestrator, Maestro, Document Understanding, AI Center) or Google Cloud Platform - Hands-on experience with Azure (preferred) or other major cloud platforms for AI workloads, including MLOps tooling - Experience defining reference architectures, design patterns, and technical standards at enterprise scale Required Skills: AI, machine learning in production environments, Healthcare technology, Cloud infrastructure, Software development tools, Large complex heterogeneous data sets, AI/ML techniques, frameworks, Data engineering best practices, Data science best practices, AI engineering best practices, MLOps, AI/ML engineering, Solution architecture, Agentic, LLM-enabled solutions, Predictive ML models, Feature engineering, Model evaluation, monitoring, Python, scikit-learn, PyTorch, TensorFlow, LangChain, LangGraph, UiPath Studio, UiPath Orchestrator, UiPath Maestro, UiPath Document Understanding, UiPath AI Center, Google Cloud Platform, Azure, Cloud platforms for AI workloads, MLOps tooling, Reference architectures, Design patterns, Technical standards at enterprise scale Benefits: 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.