Senior AIML Architect AI Program

Senior AI/ML Architects at Mayo Clinic serve at the leading edge of data systems and computer sciences embodying the convergence of technological expertise and visionary our dynamic and collaborative environment Senior AI/ML Architects are pivotal in transforming healthcare advancing patient care through cutting-edge AI solutions. By joining our team you will navigate the complexities of AI technologies data architecture and system integration crafting scalable impactful AI models and infrastructures that drive forward medical breakthroughs and improve patient outcomes.

As part of our dedicated team you will work alongside world-class professionals leveraging state-of-the-art resources to solve real-world challenges. Our commitment to excellence and innovation provides an unparalleled platform for professional growth and the opportunity to make significant contributions to the field of healthcare. If you are passionate about harnessing the power of AI to make a difference we invite you to explore our AI/ML Architect job family which includes AI/ML Architect Senior AI/ML Architect and Principal AI/ML Architect positions. Each role offers a unique opportunity to influence the future of healthcare technology and improve lives on a global scale.

Other Responsibilities May Include:
Providing strategic direction and technical leadership for complex AI Engineering initiatives.
Designing and implementing enterprise-wide AI models and solutions that address complex healthcare challenges improving patient care and outcomes.
Collaborating with cross-functional teams including data scientists engineers and healthcare professionals to seamlessly integrate AI technologies into our systems.
Evaluating and recommending new technologies to enable continuous innovation across the Center for Digital Health.
Contributing to the development of scalable and efficient data architectures ensuring the integrity and accessibility of healthcare data.
Participating in the entire lifecycle of AI solution development from concept to deployment including problem identification system architecture design implementation and evaluation.
Leading the collaboration with cross-functional teams including clinicians translation engineers software engineers and product managers to gather requirements assess feasibility define the scope requirements and deliverables of AI projects.
Providing consultative services to departments and divisions offering insights and strategies to address complex business problems.
Providing mentorship guidance and technical leadership to junior architects and engineers within the AI enablement team. May have supervisory responsibilities.

A masters degree engineering computer science health science or a related field with 10 years of experience or a bachelors degree with 12 years of experience.
At least 10 years of experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries showing an acute understanding of healthcare technology.
Demonstrated leadership in managing large projects involving complex architectures with a proven ability to navigate intricate project requirements and deliver successful outcomes.
Proficiency in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
Proficiency in multiple programming languages such as Python Java C JavaScript etc.
Considerable experience with AI/ML frameworks (e.g. TensorFlow PyTorch).
Experience using large language models as part of a solution.
Deep understanding of cloud computing platforms (GCP AWS Azure).
Rich understanding of data structures algorithms and Good Machine Learning Practices (GMLP)
A commitment to mentoring and training less-experienced team members coupled with strong interpersonal communication and time management skills.
Demonstrated risk assessment and management capability establishing robust testing strategies for technology solutions.
Deep understanding of data use and data security in healthcare.
Acute awareness of best practices in the data engineering data science AI Engineering and MLOps communities.

Preferred qualifications:
A PhD or other doctorate degree is preferred.
Advanced AI machine learning and data analytics knowledge applicable to solution architecture and development.
Demonstrated experience developing and deploying machine learning systems in the cloud (e.g. Google Cloud AWS Microsoft Azure).
In-depth knowledge of healthcare domain including clinical workflows electronic health records (EHR) medical terminologies regulatory requirements (e.g. HIPAA GDPR) and industry standards (e.g. HL7 DICOM).
Understanding of regulatory standards and compliance frameworks with the ability to effectively adapt these to different project environments.
Excellent communication collaboration and stakeholder management skills with the ability to effectively engage with diverse stakeholders and translate complex technical concepts and results to non-technical audiences.