Senior Applied AI/ML Scientist - Search Ranking

About the role

Faire is a technology wholesale platform connecting independent retailers worldwide. As a Senior Applied AI/ML Scientist on the Search team, you will help shape the technical vision, machine-learning algorithm strategy and system design behind search, the main tool customers use on the site. You will advance real-time search and recommendation systems that return personalized products and brands for every query, working with scientists and engineers in a high-scale, multi-modal environment.

Key responsibilities

• Build next-generation search ranking algorithms using 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 intent.
• Partner with teams across Faire to experiment and improve ML models for search ranking and beyond.
• Design and productionize natural-language search and discovery systems so intelligent agents can generate personalized collections, explain results and help retailers browse, filter and evaluate.
• Share best practices on deep learning model development, agent-workflow evaluation and MLOps, and mentor teammates through code reviews and technical guidance.

Required profile

• 5+ years of experience building large-scale ML models with business impact and shipping solutions to production, including 3+ years in search, recommendation or ads ranking.
• Master's or PhD in Computer Science, Statistics or a related STEM field.
• Product-focused mindset, moving quickly from research papers to prototypes and production.
• Excellent written and verbal communication and strong cross-functional influence.

Required skills

• Strong programming in Python, Java or equivalent, with deep-learning libraries such as PyTorch and big data technologies such as Spark.
• Deep understanding of ML best practices (training/serving, imbalanced data, A/B testing, feature engineering, model selection) and algorithms (user modeling, deep learning, reinforcement learning).
• Bonus: open-source contributions or peer-reviewed publications, LLM-based search experience, e-commerce or marketplace search/recommendation experience, AI coding tools (Cursor, Claude Code, Codex), and Kotlin.

What we offer

• Pay range of $211,000 to $290,500 per year in San Francisco, plus equity and benefits.
• Hybrid work: 3 days in the office (Tuesdays, Thursdays and a flex day), with remote work up to 4 weeks per year.
• Paid time off, recharge days, paid parental leave up to 16 weeks, fertility and family-building benefits, mental health support, professional development stipends and a retirement plan.