Advance Faire’s search experience with LLMs and query understanding. This hybrid position connects wholesale retailers with relevant products through intelligent retrieval.

As a Senior Applied AI Scientist, you will work across Faire’s contemporary search stack and own meaningful modeling decisions. Develop systems involving transformer-based embedding retrieval, LLM-powered query rewriting, vision-language relevance scoring, and graph-based retrieval. Lead components through production implementation and A/B testing while balancing retailer category, price point, and aesthetic context. Search scientists at Faire own models, roadmaps, and metrics for their components.

Key Responsibilities:
Develop query understanding and query rewriting systems
Build transformer-based embedding retrieval for live traffic




Score relevance with fine-tuned vision-language models
Own models, roadmaps, metrics, and production code
Use A/B tests to evaluate shipped search changes

Requirements:
Three-plus years developing production machine learning systems
Meaningful search or retrieval-and-relevance experience
Experience serving models on real user traffic
Robust Python and production engineering capability
Ability to communicate with scientists, engineers, and product managers

Use applied AI, query understanding, and relevance modeling to improve how Faire retailers discover wholesale products.
J-18808-Ljbffr

📌 Senior Applied Ai Scientist Search Toronto
🏢 Faire Wholesale
📍 Toronto