Augmented commerce: Machine learning at Shopify (2025) - Shopify

What this post added

This post details the application of machine learning at Shopify, expanding on recommender systems for merchants. It introduces the use of finetuned Qwen multimodal models for product classification and enrichment, fraud detection models inspired by Feature Space, LLaMa and general models for the Sidekick merchant assistant, Nomic embeddings for product catalog vector representations, tabular transformer models for GMV forecasting, HSTU architecture for behavior modeling, and small language models for query rewriting. It also highlights investments in GPU infrastructure (GCP, Nebius), partnerships for GPU computation acceleration (CentML), data annotation services (Toloka), and early access to frontier models.