Staff Applied AI/ML Scientist

About the role

Faire is a technology wholesale platform that connects independent retailers with products from around the world, using machine learning and data insights. Its Applied AI/ML Scientists build algorithms for recommender systems, spend optimization, lifetime value (LTV) prediction and more. As a Staff Applied AI/ML Scientist tech lead, you will own vision, strategy and execution for problems powering the two-sided marketplace, work across structured and unstructured data (personalization, recommendations, causal inference, LTV modeling, information extraction, LLMs), lead cross-functional workstreams and mentor or manage other scientists.

Key responsibilities

• Drive data science vision, strategy and execution end-to-end, acting as a pod lead across cross-functional workstreams.
• Build personalized recommendation, retrieval and ranking models, and content and retailer-level embeddings for better discovery.
• Optimize marketing, acquisition and incentive spend through targeting and personalization, measuring effectiveness with experimentation and causal inference.
• Predict lifetime value to prioritize sales and acquisition effort and personalize the new-user experience.
• Improve cold-start recommendations and exploration for new users and new selections.
• Extract insights from internal and external data (reviews, search behavior, referrals, third-party sources) to enrich leads.
• Use deep learning, multi-modal LLMs and human-in-the-loop training to understand listings and content and extract structured attributes.
• Build detection, enforcement and quality systems that reduce bad experiences (counterfeits, policy violations, poor service quality).
• Re-engage users through personalized marketing and identify engagement gaps and opportunities.
• Mentor or manage Senior Applied AI/ML Scientists and Analytics Engineers.

Required profile

• 5+ years of industry experience applying machine learning to real-world problems.
• Experience with e-commerce, marketplaces, growth, personalization, incentives or trust and quality.
• Experience as a tech lead, mentoring scientists or ML engineers, and leading model development without supervision.
• Strong communication skills and ability to work in a highly cross-functional team.
• Willingness to learn new tools and techniques.

Required skills

• Causal inference, predictive/LTV modeling, recommendations, information extraction, entity resolution and/or deep learning and LLMs.
• Strong programming skills.

What we offer

• Pay range of $246,500 to $339,000 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, comprehensive health coverage, fertility and family-building benefits, mental health support, professional development stipends and a retirement plan.