Unifying Ads Engagement Modeling Across Pinterest Surfaces

Pinterest unified three separate ads engagement models for Home Feed, Search, and Related Pins into one shared architecture.

• •Three diverged surface models caused low iteration velocity, redundant training costs, and high maintenance overhead
• •Unification followed three principles: start simple with merged components, iterate incrementally with surface-aware features, and maintain operational safety
• •Surface-specific calibration layers for HF and SR outperformed a single global calibration layer
• •Multi-task learning with surface-specific checkpoint exports enabled shared representation while allowing per-surface iteration
• •Efficiency improved via DCNv2 projection layers, fused kernel embedding, TF32 training, and request-level user embedding broadcasting