It is an exciting time at Mayo Clinic, as we are building the most trusted generative AI and LLM-based solutions to empower our staff, improve our practice and transform healthcare. To accelerate our generative AI strategy, we are forming a cross functional team of technical experts. This team will be responsible for:
• Building the most trusted generative AI and automation solutions to benefit patients worldwide.
• Providing temporary tiger-team efforts to accelerate key initiatives.
• Expanding the organization’s understanding of LLM technology through:
- Development of best practices, knowledge assets, and code examples to accelerate the efforts of others.
- Execution of technical proofs of concept and exploration
• Providing consultations, presentations, and sharing of knowledge across Mayo Clinic to technical and non-technical audiences
• Providing guidance across the Generative AI program workstreams as technical experts
Position Responsibilities:
• Contribute to MLOps Infrastructure: You'll help develop and maintain scalable and robust MLOps pipelines and platforms using cloud services (Azure, GCP, On-prem) and containerization technologies (Docker, Kubernetes).
• Model Deployment & Monitoring: You'll support the deployment of machine learning models into production environments and assist in establishing monitoring solutions for model performance, data drift, and system health.
• Automation & CI/CD: You'll work on automating the machine learning lifecycle, including data ingestion, model training, validation, and deployment using CI/CD practices.
• Collaboration: You'll collaborate closely with Data Scientists, Machine Learning Engineers, and other Software Engineers to understand their needs and provide MLOps solutions.
• Documentation & Best Practices: You'll contribute to documenting MLOps processes, best practices, and system architecture.
• Troubleshooting & Support: You'll participate in troubleshooting and resolving issues related to MLOps pipelines and deployed models.
• Learn & Grow: You'll continuously learn and stay updated with the latest MLOps tools, technologies, and methodologies.
This is a full-time hybrid position within the United States. Most work will be completed remotely but at times the incumbent will need to be on the Rochester, MN campus. Therefore the incumbent must live within a reasonable driving distance of the campus.
Mayo Clinic will not sponsor or transfer visas for this position including F1 OPT STEM. Incumbent must live within the United States.
Bachelor's Degree in Computer Science/Engineering or related field; Or an Associates’ degree in Computer Science/Engineering or related field with an additional 2 years of experience as described below.
Have working knowledge and experience of Software Engineering with a minimum of internships and a minimum of 1 yr. of experience, or 2yrs of experience coding applications or services in a high-level language (C, C++, Golang, Java, C# etc.). Demonstrated problem solving and time management skills. Possesses strong technical aptitude for designing and implementing software solutions. Experience with modern application development frameworks. Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Deep hands-on technical expertise, excellent verbal and written communication skills. Experience with Agile software development techniques. Preferred qualifications for this position include: Ability to use a wide variety of open-source technologies and cloud-based services. Experience with Google and Azure cloud environments. Experience in databases, analytics, big data systems or business intelligence products· Experience with building high-performance, highly available and scalable distributed systems. Experience developing software for healthcare related industries.
Preferred Qualifications:
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Company:
Mayo ClinicEmployee Type:
Full timeLocation:
United StatesSalary:
$ 123199 - $ 228800