Tech Stack

Description

You will lead the development of machine learning systems powering Cedar's Personalization Engine, owning the end-to-end ML lifecycle, from modeling to MLOps. You'll combine hands-on technical work with people management to optimize patient journeys for financial resolution and positive experience.

Requirements

• 6+ years of production ML engineering experience
• Built ML personalization or recommendation systems at scale for consumer products
• Expertise in Python and SQL
• Experience with MLOps infrastructure
• Strong software engineering and system design skills

Responsibilities

• Own ML system end-to-end for reliability, scalability, and effectiveness
• Execute full-stack ML including MLOps and modeling (ensemble, RL, bandits)
• Conduct code/design reviews and manage two ML engineers
• Improve feedback loop for autonomous model adaptation
• Partner with Product and Design to define ML problems