Senior MLOPS/DEVOPS Engineer - CDH - Remote

Senior MLOps/DevOps Engineers at Mayo Clinic serve at the union of data, systems, and computer sciences as part of product teams that design, develop, and deploy AI-driven solutions to improve patient health and clinic operations. Senior MLOps/DevOps Engineers may work with knowledge architects, informaticians, and clinicians within Mayo, as well as partnered outside companies to develop and deploy applications to bring AI and analytic solutions to nontechnical users, often at the point of care.

As a Senior MLOps/DevOps Engineer at Mayo Clinic, you will be at the forefront of working with teams to innovate AI-driven solutions that enhance patient care and clinic operations. In this pivotal role, you'll lead the charge in developing, integrating, and standardizing software components, ensuring our digital health technology products meet and exceed regulatory requirements, and setting new benchmarks for safety and effectiveness in clinical settings. You will also contribute to the development of new AI methods and technologies that can advance the state-of-the-art in healthcare AI.

The day-to-day work involves collaborating with a multidisciplinary team, including clinicians, knowledge architects, translation engineers, product managers, and external partners to make sophisticated AI and analytics solutions accessible to non-technical users. You'll guide the engineering of systems that are pivotal to developing and deploying these solutions, encompassing everything from design requirements, component creation, verification, non-clinical validation, and risk mitigation to the creation and maintenance of quality system procedures. Your expertise will also extend to facilitating consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines.

This role is instrumental in providing consultative services to departments and divisions, offering insights into complex business problems. Your ability to communicate complex findings in easily understandable terms will bridge the gap between sophisticated AI technologies and practical clinical applications.

Roles and Responsibilities

• Build, test and maintain the infrastructure and tools to facilitate the consistent and automated AI software solution development and release process.
• Design, build and maintain the ML CI/CD pipeline that automates data collection, data analysis, experimentation, model training, model serving and monitoring in production.
• Lead the interpretation of data analysis to inform strategic decisions and communicate complex findings in easily understandable terms to bridge the gap between AI technologies and clinical applications.
• Achieve continuous delivery of AI software solution and updates to production at scale.
• Collaborate with data scientists, engineers, product teams and other key stakeholders.
• Provide consultative services to clinical work units, offering insights and strategies to address complex business problems.
• Actively seek ways to improve software development and operation process.
• Provide mentorship, guidance, and technical leadership to junior engineers within the AI enablement team. May have supervisory responsibilities.

This position will accept applications until 5/7/2024. This deadline may be extended if the necessary candidate pool is not met by this date.

Bachelor’s degree in Computer Science or a related field with 7 years of experience. Or Master’s degree in Computer Science or a related field with 5 years of experience.
Strong DevOps, Data Engineering and ML background. Familiar with best practices in the data engineering and MLOps community.
Experience building and maintaining CI/CD pipelines. Demonstrated experience on a broad range of DevOps tools such as Ansible, Docker, Kubernetes, Jenkins etc.
Experience building, deploying and maintaining ML models in production. Experience with MLOps tools such as ModelDB, MLFlow and Kubeflow.
Familiarity with python tools for data science.
Experience with cloud infrastructure. Experience with Google Cloud Platform a plus.
Excellent communication and teamwork skills.
Ability to collaborate effectively with internal business stakeholders, outside partners and technology teams.