Pinterest Labs

Recommender Systems

Pinterest's recommendation systems are built on three core principles: leveraging lifelong user activity sequences to understand evolving preferences, deploying unified models that serve multiple tasks and surfaces for consistency, and maintaining infrastructure budget-aware costs to ensure sustainable scale across hundreds of millions of users.

Our most recent advances include lifelong user sequence modeling that captures nuanced behavioral patterns over extended periods, foundation ranking models that generalize across diverse recommendation scenarios, and generative recommender systems that create personalized content experiences.

Featured Posts

Join us and create the career you love

Work in a collaborative, open-ended, publish-friendly environment, and build AI technology on top of the rich visual graph structure inherent to Pinterest, and ship products to 550M+ users.

Explore jobs
people together