Staff Machine Learning Engineer

Root is on a mission to unbreak insurance by creating experiences people love at prices they can’t believe. We believe that investing in world-class technology will facilitate a new class of insurance products, driving a massive positive impact on the hundreds of millions of drivers who carry auto insurance in the US. Root’s Engineering team is committed to building a flexible platform on which our product designers and quantitative scientists can quickly test ideas, deploy them into production, and iterate, with the ultimate objective of a delightful customer experience coupled with effective risk management. The Opportunity Price is the most important component of an insurance product, with the ability to drive customer delight through lower prices unlocked by state-of-the-art predictive modeling. The Pricing Platform team owns the foundational technology that powers the R&D and production lifecycle for Root’s most critical machine learning models. This platform is a cornerstone of Root’s strategic goal of becoming the best in the world at pricing and automation. In this role, you will help build the next generation of Root’s machine learning platform for pricing, creating the infrastructure that allows researchers to move rapidly from experimentation to production. You will work closely with researchers on problems including feature pipelines and feature stores, reproducible model training and orchestration, model registries and versioning, automated validation, model serving, production observability, and tooling that ensures consistency between research and production. You will also explore how emerging LLM technology can revolutionize the data science workflow, improving the way models are developed, tested, deployed, and maintained, with the goal of dramatically reducing the time and effort required to turn new research into production pricing models. As a Staff Machine Learning Engineer , you are the technical leader of the team, owning long-term architectural design of the platform, the versioned contracts between data, features, models, and pricing, and the technical strategy that makes pricing models deployable with self-serve technology. Your influence is cross-team, spanning platform teams, their dependencies, and the interface with Data Science and Actuarial. This is a hands-on role. You design, you write and review code in the most critical parts of the system, and you are accountable for the technical coherence of the platform over time....

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