ecommerce_ops · workflow
Trendyol ensembles Mixture-of-Experts neural networks and LTR GBDTs for e-commerce search ranking
Trendyol's single-model ranking architecture could not simultaneously capture both engagement-specific behavioral signals and high-precision tabular features, leaving gaps that neither model family alone could fill.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User search triggers pipeline
A user search query initiates the ranking pipeline, which is the primary bridge between millions of users and an ever-changing catalog.
Tools used
Mixture-of-Experts NNsLearning-to-Rank GBDTsTorchTriton
Outcome
The rank-blend mean ensemble was the clear winner in A/B tests across all platforms, delivering statistically significant uplifts across key user actions and downstream conversion objectives.
Grounding & classification
Source type: technical build writeup
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