Senior Principal AI/ML Engineer - AI Program

About the role

AI/ML Engineers at Mayo Clinic play a pivotal role in the union of data, systems, and computer sciences. They work closely with a multidisciplinary team, including clinicians, user experience designers, product managers, IT professionals, and external partners, to develop and deploy effective, efficient, and ethical AI/ML solutions into clinical practice to enhance patient care and operational efficiency.

Responsibilities

• Lead the full spectrum of the AI life cycle from ideation to production.
• Understand the clinical environment well, including workflows, challenges, and requirements of healthcare providers and patients.
• Leverage advanced techniques in AI/ML to analyze vast amounts of healthcare data, including patient records, medical imaging, and genomic information, and other multimodal data sources, to develop AI solutions that meet clinical needs and are integrated smoothly into clinical processes.
• Develop, integrate, and standardize software components and create, maintain, and follow quality system procedures.
• Guide the engineering of systems that are pivotal to developing and deploying these solutions and provide technical leadership on model architecture decisions, including multimodal learning approaches, model adaptation strategies, evaluation methodologies, interpretability techniques, and performance optimization for clinical AI systems.
• Evaluate and guide architectural choices involving vision encoders, multimodal fusion approaches, representation learning, and model adaptation strategies.
• Evaluate and guide architectural choices involving vision encoders, multimodal fusion approaches, representation learning, and model adaptation strategies.
• Evaluate and guide architectural choices involving vision encoders, multimodal fusion approaches, representation learning, and model adaptation strategies.
• Evaluate and guide architectural choices involving vision encoders, multimodal fusion approaches, representation learning, and model adaptation strategies.
• Ensure compliance with ethical guidelines, regulatory requirements, and data privacy standards in the development and deployment of AI solutions by the AI development team.
• Oversee the engineering of systems crucial for developing and deploying AI solutions.
• Facilitate consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines.
• Provide mentorship, guidance, and technical leadership to junior engineers within the AI enablement team.

Qualifications

• A master’s degree in engineering, computer science, mathematics, health science, or a related field with 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.
• Demonstrated leadership in managing complex projects, with a proven ability to navigate intricate project requirements and deliver successful outcomes.
• Proven success in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
• Expertise with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
• In-depth knowledge of healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards.
• Strong skills in AI/ML techniques and frameworks.
• Demonstrated leadership in administration, education, software development, and technical reporting.
• Experience mentoring and training less-experienced team members, coupled with strong interpersonal, communication, and time management skills.