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.
As an Associate AI/ML Engineer, you may work on the full spectrum of the AI life cycle from ideation to production, under the guidance of senior members of the team. You will understand the clinical environment well, including workflows, challenges, and requirements of healthcare providers and patients. You will leverage advanced techniques in AI/ML to analyze vast amounts of healthcare data, including patient records, medical imaging, and genomic information, to develop AI solutions that meet clinical needs and are integrated smoothly into clinical processes. You will develop, integrate, and standardize software components and create, maintain, and follow quality system procedures. You will work on the engineering of systems that are pivotal to developing and deploying these solutions, which encompass everything from design requirements, development, component creation, verification, non-clinical validation, and risk mitigation to ensure our digital health technology products meet and exceed regulatory requirements and setting new benchmarks for safety and effectiveness in clinical settings. Your will participate in consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines.
- Working on component design, development, integration, and standardization to create AI-driven solutions that seamlessly integrate into clinical practice to enhance patient care and clinic operations.
- Supporting governance reviews under the guidance of senior team members while developing expertise in AIA requirements, review methodologies, and governance precedent.
- Assisting with review documentation, stakeholder communications, issue tracking, and maintenance of governance records.
- Participating in structured training, consultation, and review activities designed to build increasing independence and technical judgment.
- Collaborating with a multidisciplinary team, including clinicians, user experience designers, product managers, and IT professionals, to understand user needs, workflows, and clinical requirements and assess feasibility. Translating user feedback and requirements into design concepts and usability specifications for AI solutions.
- Interpreting / analyzing data to inform strategic decisions and communicate complex findings in easily understandable terms to bridge the gap between AI technologies and clinical applications.
- Leveraging machine learning techniques such as deep learning, natural language processing, computer vision, large language models, etc., to design, develop and deploy end-to-end AI solutions for healthcare applications.
- Participating in the engineering of systems crucial for developing and deploying AI solutions.
- Participating in consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines.
- Contributing to implementing the best practices and standards for AI development and deployment methodologies, tools, and platforms.
