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
- Strong 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.

📌 Senior Applied AI Scientist Search (Toronto)
🏢 Faire Wholesale
📍 Toronto