MLOps Engineer

Strategic Healthcare Programs (SHP) is a leading provider of analytics and performance management solutions for the post-acute healthcare market. We are an industry leader in helping Home Health, Hospice, and Skilled Nursing providers improve their financial and quality performance while complying with many regulatory requirements. Additionally, we connect the post-acute world to the broader provider markets to allow for optimal management across the continuum of care.

Role Overview

We're hiring a strong Python engineer to build and operate our production ML platform end-to-end. You'll productionalize data science work by building robust on-premises infrastructure, establishing software engineering best practices, and creating the tooling that enables our data scientists to ship faster. All infrastructure is self-hosted.

This is a remote or hybrid position within the United States. Employees living within 75 miles of the Santa Barbara office are required to work in-person in the office every Wednesday.

ML experience is welcome but not required.

We care most about your software engineering foundation: production Python, OOP, testing, and async/parallel performance. Our existing ML engineers will get you up to speed on the ML side — frameworks, LLMs, vector stores, vLLM, and the rest.

Team

You'll join a tight ML team where every engineer owns meaningful surface area. We're a small team where every engineer owns their code end-to-end. We value people who deeply understand the systems they build — not just that they run.

What You'll Do Day-to-Day

Production ML Systems (40%)

• Build automated ML pipelines: data ingestion training evaluation deployment retraining
• Deploy and serve models (batch + real-time) via FastAPI/Flask APIs with auto-scaling and rollback
• Implement CI/CD for ML: model packaging, versioning, automated deployments
• Optimize workflows using async, parallelism, Ray, and Dask

**ML Platform & Tool...