Lead the end-to-end development and operation of machine learning systems supporting customer retention, ranking, matching, recommendations, pricing, and lifetime value growth. Build scalable data pipelines and ML infrastructure across batch and real-time environments, while implementing model monitoring, observability, deployment, and performance optimization. Collaborate across engineering and science teams and promote strong software engineering practices.

Own and architect the core ranking system end-to-end: model design, production reliability, automated retraining, bias mitigation, personalization, and cross-functional technical leadership. Mentor engineers, drive roadmap, and scale experimentation and ML infrastructure.