MLOps Lead - Remote Health AI & Cloud Ops

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

Benefits offered by this job

Sign-on bonus

Relocation bonus (where applicable)

Annual Pay for Performance (AP4P) plan

Job summary

Intermountain Health—SelectHealth Murray is seeking a hands-on Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML products. The role oversees AI/ML engineering, data engineering, software engineering, and cloud operations to reduce costs and improve member health and experience.

The ideal candidate will mentor teams, drive the MLOps roadmap, enforce responsible AI practices, and deliver projects that meet clinical and technical needs.

Qualifications

• Demonstrated experience delivering ML ops infrastructure and solutions.
• CI/CD practices with Docker, Kubernetes, Git.
• IaC tools such as Terraform and Databricks Asset Bundles.
• Strong leadership and stakeholder engagement skills.
• Knowledge of ML methodologies, algorithms and frameworks.

Responsibilities

• Oversee strategic direction of the MLOps tech stack.
• Lead AI/ML data and software engineering, cloud operations, and security teams.
• Ensure Responsible AI governance and explainability.
• Drive AI/ML roadmap and project execution across the company.
• Coordinate ML operations and data engineering product development.
• Mentor ML engineering leads and build high-performing teams.
• Deliver timely, high-quality ML solutions aligned with clinical and business needs.
• Integrate ML solutions into core business processes.

Skills

Machine Learning Operations

Cloud Platforms

Artificial Intelligence and Machine

Team Leadership

Programming and CI/CD Best Practices

Education

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

Job description

Intermountain Health—SelectHealth Murray is seeking a hands-on Machine Learning Operations Manager to lead deployment and monitoring of enterprise ML products. The role oversees AI/ML engineering, data engineering, software engineering, and cloud operations to reduce costs and improve member health and experience.

The ideal candidate will mentor teams, drive the MLOps roadmap, enforce responsible AI practices, and deliver projects that meet clinical and technical needs.