Machine Learning Engineer, Consumer Alliance

Build and operate the production recommender stack for menu personalization, covering feature pipelines, training workflows, model serving, experimentation tooling, and underlying infrastructure. Transition research into reliable systems with real latency, scalability, and observability needs, maintain end-to-end accountability for key components, and continuously improve performance based on production signals. Partner closely with Data Scientists, Data Engineers, Backend Engineers, and Product to support roadmap-driven personalization improvements.