Head of MLOps & AI Platform (Remote)

Intermountain Healthcare Inc.; Nevada; Remote; USD 82,000 - 127,000; Full time

Benefits offered by this job

Sign-on bonus

Relocation bonus

Annual Pay for Performance (AP4P) plan

Job summary

Intermountain Health is seeking a Machine Learning Operations Manager to lead a team of ML and data engineers, delivering scalable MLOps deployments and monitoring across enterprise systems. The role combines hands-on leadership with strategic oversight of the ML tech stack, AI/ML governance, and collaboration with business and technical leaders to advance efficient, values-driven health outcomes.

The position allows remote work with periodic travel and requires strong CI/CD, cloud, and MLOps

Qualifications

• Experience delivering machine learning operations infrastructure and solutions.
• Proficiency with CI/CD, Docker, Kubernetes, and Git.
• Experience with IaC tools such as Terraform and Databricks Asset Bundles.
• Leadership ability to motivate and guide high-performing teams.
• Excellent communication with senior stakeholders.

Responsibilities

• Oversee MLOps tech stack strategy and direction.
• Coordinate AI/ML engineering, data engineering, and cloud operations.
• Ensure responsible AI practices across internal and 3rd party models.
• Lead and mentor ML operations engineers and data engineers.
• Deliver timely, high-quality ML solutions aligned with clinical and business needs.
• Integrate ML solutions into enterprise processes with governance and explainability.

Skills

Machine Learning Operations

Cloud Platforms

Artificial Intelligence and Machine L​

Education

Bachelor's degree in AI, ML, Computer Science, Statistics, or related field

Tools

Docker

Kubernetes

Git

Terraform

Databricks Asset Bundles

Job description

Intermountain Health is seeking a Machine Learning Operations Manager to lead a team of ML and data engineers, delivering scalable MLOps deployments and monitoring across enterprise systems. The role combines hands-on leadership with strategic oversight of the ML tech stack, AI/ML governance, and collaboration with business and technical leaders to advance efficient, values-driven health outcomes.

The position allows remote work with periodic travel and requires strong CI/CD, cloud, and MLOps