Senior Applied AI/ML Scientist - Marketplace Quality

About the role

Faire is a technology wholesale platform connecting independent retailers worldwide with products from around the world. Its Applied AI/ML Scientists build algorithmic solutions for notification and recommender systems, advertising attribution and LTV predictions. As a Senior Applied AI/ML Scientist on the Marketplace Quality team, you will own the modeling and measurement that keeps the marketplace trustworthy for hundreds of thousands of brands and retailers, matching the catalog against external data at scale, detecting pricing and policy violations with calibrated confidence and deciding which ones to act on within a constrained operations budget.

Key responsibilities

• Own applied ML projects end-to-end: frame the problem, build and ship the model, and measure its impact on the marketplace.
• Build and improve pricing-integrity models that compare listings against external pricing signals and detect over- and under-pricing violations.
• Solve product matching and entity resolution at scale using text and image embeddings, retrieval and multi-modal LLMs, and build match-quality and gating models.
• Extract structured attributes from unstructured listing content (descriptions, images, third-party sources).
• Turn model scores into action by designing targeting and prioritization logic that ranks violations by expected impact against the cost of false positives.
• Build human-in-the-loop systems with marketplace operations partners: audits, training labels, precision bars and feedback loops.
• Design and analyze experiments for enforcement levers such as downranking, badging and brand-facing remediation, and measure effects on retailer trust and GMV.
• Partner with product, engineering, operations and analytics to turn models into shipped product.

Required profile

• 3+ years of industry experience applying machine learning to real-world problems.
• Experience with e-commerce, marketplaces, catalog and content quality, search or personalization.
• Ability to drive a project end-to-end and lead model development with limited supervision.
• Strong communication skills and ability to work in a cross-functional team.

Required skills

• Deep learning and LLMs, computer vision, information extraction, entity resolution, ranking and/or experimentation and causal inference.
• Strong programming skills.
• Great to have: a Master's or PhD in CS, Statistics or a related STEM field; catalog quality, product attribute extraction or e-commerce computer vision experience; LLM evaluation pipeline experience.

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 up to 4 weeks of remote work per year.
• Paid time off, recharge days, paid parental leave up to 16 weeks, fertility and family-building benefits, mental health support, stipends and a retirement plan.