Remote MLOps Lead for Enterprise AI

Intermountain Healthcare Inc.; Murray (UT); Remote; USD 83,000 - 127,000; Full time

Job summary

Intermountain Health is seeking a Machine Learning Operations Manager to lead deployment, monitoring, and governance of enterprise ML solutions. You will mentor ML, data, and software engineers, steer the MLOps roadmap, and collaborate with cybersecurity and cloud operations to deliver cost reductions and health improvements.

The role emphasizes responsible AI, scalable deployment, and alignment with clinical and business needs, with remote work option and travel as needed.

Qualifications

• Experience delivering and implementing ML operations infrastructure and solutions.
• Experience with CI/CD practices and tools (Docker, Kubernetes, Git).
• Experience with Infrastructure-as-Code (Terraform).
• Strong leadership and ability to motivate high-performing teams.
• Excellent communication with senior stakeholders.
• Solid understanding of ML methodologies, algorithms, and frameworks.

Responsibilities

• Oversee the MLOps tech stack and strategy.
• Lead AI/ML eng, data eng, software eng, and cloud ops teams.
• Ensure responsible AI monitoring and governance across ML solutions.
• Coordinate ML ops project portfolio for timely delivery across business needs.
• Develop and coach ML ops engineers and managers.
• Integrate ML solutions into core enterprise processes with governance.

Skills

Leadership

CI/CD

Docker

Kubernetes

Git

Terraform

Databricks

Python

SQL

Cloud Platforms

Education

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

Tools

Docker

Kubernetes

Git

Terraform

Databricks

Spark

TensorFlow

MLFlow

LangChain

Job description

Intermountain Health is seeking a Machine Learning Operations Manager to lead deployment, monitoring, and governance of enterprise ML solutions. You will mentor ML, data, and software engineers, steer the MLOps roadmap, and collaborate with cybersecurity and cloud operations to deliver cost reductions and health improvements.

The role emphasizes responsible AI, scalable deployment, and alignment with clinical and business needs, with remote work option and travel as needed.