TLDR Tech / Data
How we rebuilt search ranking at Faire with deep learning
Faire rebuilt its search ranking stack from XGBoost to deep learning to better optimize competing goals like relevance, freshness, brand discovery, and cross-surface consistency. The migration required reworking data pipelines, observability, and production serving, including custom Docker-based infrastructure, shared-memory embeddings, and CPU sandboxing to cut startup latency from 20–30 minutes to a few minutes. The new stack delivered measurable gains, including a ~2% order volume boost on Product Search.
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