Senior Applied AI/ML Scientist - Search Ranking
Faire · San Francisco, CA
About this role
**Senior Applied AI/ML Scientist — Search Ranking** **About Faire** Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we use tech, data, and machine learning to connect entrepreneurs worldwide—helping retailers discover great products from around the world to sell in their stores. **About the role** As a **Senior Applied AI/ML Scientist** on the **Search** team, you’ll shape the technical vision, ML algorithm strategy, and system design behind one of Faire’s most important growth levers: **Search**. You’ll advance real-time search and recommendation systems that power next-generation shopping experiences. You’ll work at the frontier of algorithms—combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data—to return hyper-relevant, personalized products and brands for every user query. **What you’ll do** - Build next-generation **Search ranking algorithms** by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey. - Leverage **LLMs** to extract multimodal signals (**text, visual**) to better profile users and their intents. - Partner across Faire to experiment with and improve ML models for search ranking and beyond. - Design and productionize **natural-language search and discovery systems** so intelligent agents can generate relevant, personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation. - Share best practices across deep learning model development, agent-workflow evaluation, and **MLOps**; help teammates level up through code reviews and technical guidance. **You’re a great fit if you have…** - **5+ years** of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including **3+ years** in search, recommendation, or ads ranking. - A **Master’s or PhD** in Computer Science, Statistics, or a related STEM field. - Strong programming skills (**Python, Java, or equivalent**) and hands-on experience with deep-learning libraries (e.g., **PyTorch**) and big data technologies (e.g., **Spark**). - Deep understanding of ML best practices (training/serving, imbalanced data, A/B testing, feature engineering, feature/model selection) and algorithms (user modeling, deep learning, reinforcement learning) with applications in search, recommendation, and advertising. - A product-focused mindset and a bias toward execution—moving quickly from research to prototypes and production. - Excellent written and verbal communication skills and strong cross-functional influence. **Bonus points for…** - Contributions to open-source ML libraries or peer-reviewed publications in ML/AI. - Experience developing and productizing **LLM-based** applications and systems in the search domain. - Experience building search and recommendation systems for e-commerce or two-sided marketplaces. - Experience using AI tools (e.g., **Cursor, Claude Code, Codex**) for code development and daily productivity. - Familiarity with **Kotlin**. **Salary Range** - **San Francisco:** $211,000 to $290,500 per year - This role may also be eligible for equity and benefits. Actual base pay depends on transferable skills, work exp
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