Remote MLOps Lead: Scalable AI Deployment

Intermountain Healthcare Inc.; Trenton (NJ); Remote; USD 82,000 - 127,000; Full time

Job summary

Intermountain Health and Select Health in Murray, Utah, seek a Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML solutions. The role blends hands-on delivery with team leadership to drive cost reductions and improved member health and experience.

You will mentor ML engineers and data engineers, align AI strategy with business goals, and oversee a portfolio of ML ops projects.

Qualifications

• Demonstrated experience of delivering and implementing successful machine learning operations infrastructure and solutions.
• Experience with CI/CD and tools such as Docker, Kubernetes, and Git.
• Experience with Infrastructure-as-Code tools such as Terraform and Databricks Asset Bundles.
• Strong leadership skills with the ability to motivate and guide high-performing teams.
• Excellent communication with senior stakeholders and knowledge of MLOps best practices.

Responsibilities

• Accountability for strategic direction of MLOps tech stack.
• Manage AI/ML, data and software engineering teams and align with business and technical leaders.
• Ensure Responsible AI practices for monitoring internal and 3rd party ML solutions.
• Lead and coach ML operations leads in team culture and project execution.
• Oversee ML operations projects portfolio ensuring timely, quality delivery.
• 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/CS

Tools

Docker

Kubernetes

Terraform

Databricks Asset Bundles

Spark

TensorFlow

MLFlow

LangChain

Job description

Intermountain Health and Select Health in Murray, Utah, seek a Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML solutions. The role blends hands-on delivery with team leadership to drive cost reductions and improved member health and experience.

You will mentor ML engineers and data engineers, align AI strategy with business goals, and oversee a portfolio of ML ops projects.