Head of ML Operations & Deployment (Remote)

Intermountain Healthcare Inc.; Utah; Remote; USD 69,000 - 165,000; Full time

Job summary

Intermountain Health is seeking a Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML solutions. You will mentor teams across ML engineering, data engineering, and software disciplines, aligning with business goals and responsible AI practices.

The role emphasizes collaboration with clinical and technical leaders, governance, and scalable cloud-based ML platforms to reduce costs and improve member health outcomes.

Qualifications

• Bachelor's degree in AI, ML, Computer Science, Statistics, or a related field.
• 5+ years of experience in machine learning, data science, data engineering, or software engineering.
• Experience in health insurance, population health, or related industry.
• Strong written and verbal communication skills.

Responsibilities

• Lead and mentor a team of ML operations engineers and data engineers responsible for deployment and monitoring of enterprise ML solutions.
• Coordinate AI/ML engineering, data engineering, software engineering, cybersecurity, and cloud operations with business and technical leaders.
• Ensure responsible AI practices, model governance, and explainability across solutions.
• Oversee the ML operations portfolio to deliver timely, high-quality ML deployments that align with clinical and business needs.
• Develop and execute an AI/ML strategic vision and roadmap.

Skills

Leadership

Communication

CI/CD

Cloud

Python

Stakeholder management

Education

Bachelor's degree in AI/ML/CS/Statistics

Tools

Docker

Kubernetes

Terraform

Databricks

MLFlow

Job description

Intermountain Health is seeking a Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML solutions. You will mentor teams across ML engineering, data engineering, and software disciplines, aligning with business goals and responsible AI practices.

The role emphasizes collaboration with clinical and technical leaders, governance, and scalable cloud-based ML platforms to reduce costs and improve member health outcomes.