Machine Learning Engineer

Develop and deploy ML models across multiple problem domains including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection in production environments serving millions of rides. Build and iterate on agentic AI systems that automate decision-making and reduce operational overhead. Design feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform. Partner with Data Scientists on the Algorithms and Decisions teams to scale research prototypes into production. Evaluate system performance against business KPIs, run experiments, and drive continuous model improvement. Identify new opportunities where ML can create leverage across Lyft Business verticals and pitch solutions. Contribute to team engineering standards regarding code quality, observability, and testing practices. This role operates at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.