Architects, develops, and deploys high-performance machine learning systems across the full ML lifecycle. Responsibilities include building large-scale data and feature pipelines, training tree-based and deep learning models, developing low-latency inference services, implementing MLOps and monitoring, and designing rigorous experimentation. The role requires strong Python and software engineering expertise, distributed computing experience, production ML serving skills, and familiarity with statistical evaluation and A/B testing.