Remote ML Ops Engineer — Healthcare Data Platforms

Intermountain Health; Jackson (MS); On-site; USD 83,000 - 131,000; Full time

Job summary

Intermountain Health is seeking a Senior Machine Learning Operations Engineer to lead end-to-end ML platform development for clinical and operational analytics. You will partner with data scientists, engineers, and stakeholders to deploy scalable solutions that ship value while adhering to Responsible AI practices.

The role emphasizes collaboration in a remote-friendly environment, with a focus on governance, CI/CD, and productionizing models across the healthcare ecosystem.

Qualifications

• Experience leading the development of MLOps machine learning platforms leveraging model registries, feature stores, model monitoring, etc.
• Successful experience leading the development, implementation, and administration of machine learning systems and pipelines within operational workflows from end-to-end.
• Experience utilizing and creating custom API’s, functions, libraries, and/or packages in multiple programming languages.

Responsibilities

• Develop scalable ML systems enabling integration of data science applications into healthcare operations.
• Partner with data scientists, application developers, data architects, and system engineers to design ML pipelines.
• Deploy and maintain innovative data science tools resulting in measurable ROI and timely delivery.
• Lead initiatives from inception to workflow integration, engaging stakeholders across analytics, data engineering, and software teams.

Skills

AI/ML modeling techniques

MLOps platforms

Programming languages

DevOps practices

Data manipulation

Cloud Computing

Responsible AI Processing and Monito r

Education

Degree in data science / CS / engineering

Tools

Docker

Kubernetes

Git

Job description

Intermountain Health is seeking a Senior Machine Learning Operations Engineer to lead end-to-end ML platform development for clinical and operational analytics. You will partner with data scientists, engineers, and stakeholders to deploy scalable solutions that ship value while adhering to Responsible AI practices.

The role emphasizes collaboration in a remote-friendly environment, with a focus on governance, CI/CD, and productionizing models across the healthcare ecosystem.