Responsibilities
- Design, develop, and manage scalable platform systems such as feature stores, real-time inference engines, and vector databases handling millions of requests per second
- Operate and oversee online A/B testing through reliable platform tools, using system metrics and business KPIs to refine recommendation algorithms
- Work closely with domestic engineering and cross-functional groups to convert business needs into reusable platform modules and APIs
- Improve and expand the machine learning platform to enable rapid development, system growth, and responsiveness to evolving business demands
- Support onboarding, training, and mentorship of new team members in modern platform engineering practices and emerging technologies
Work Arrangement
Hybrid — California
Team
The Recommendations team enables personalized user experiences by applying advanced machine learning techniques. It focuses on delivering timely, context-sensitive suggestions that reflect individual preferences. Success depends not only on strong models but also on a resilient, adaptable ML infrastructure designed for scalability and continuous experimentation. The team builds and maintains core ML systems that are fast, dependable, and technologically advanced, combining innovation with engineering rigor to shape how users discover content.
