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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers. The company uses machine learning and data insights to help local retailers compete and thrive.
As a Senior Applied AI/ML Scientist on the Listing Quality team, you will own end-to-end modeling and measurement for Faire's product catalog—images, titles, descriptions, and structured attributes across millions of products from hundreds of thousands of independent brands. Listing quality is a high-leverage surface on the marketplace; better images and richer product information improve discoverability, evaluation, and conversion across search, recommendations, and product detail pages.
You will work primarily with unstructured data using multi-modal deep learning and large language models. Key responsibilities include:
- Own applied ML projects end-to-end: problem framing, model building and shipping, and impact measurement
- Use multi-modal deep learning and LLMs to understand listing content, extract structured product attributes, and detect quality issues at scale
- Improve product imagery through hero image selection, image ordering, cropping, and enhancement
- Build ranking and exploration approaches (e.g., bandit-style selection) that learn which content performs best for different audiences
- Improve listing text: titles, descriptions, and product information coverage, measuring downstream effects on discovery and conversion
- Build LLM-as-judge and human-in-the-loop evaluation systems with measurable accuracy bars before production deployment
- Partner across product, engineering, design, and analytics to ship models and drive business impact
- Solve challenging two-sided marketplace problems
Faire's Applied AI/ML team includes experienced scientists from Uber, Airbnb, Square, Facebook, and Pinterest. The company was founded in 2017 by early product and engineering leads from Square and is backed by Y Combinator, Lightspeed, Forerunner, Khosla, Sequoia, Founders Fund, and DST Global. Headquarters are in San Francisco with offices in Kitchener-Waterloo, Toronto, London, and New York.
Hybrid employees work in-office three days per week (Tuesdays, Thursdays, and one flex day) with flexibility to work remotely up to four weeks annually.
QUALIFICATIONS:
- 3+ years of industry experience using machine learning to solve real-world problems
- Experience with relevant business problems: e-commerce, marketplaces, catalog and content quality, search, or personalization
- Experience with relevant technical methods: deep learning and LLMs, computer vision, information extraction, entity resolution, ranking, and/or experimentation and causal inference
- Strong programming skills
- Excitement and willingness to learn new tools and techniques
- Ability to drive projects end-to-end and lead model development with limited supervision
- Strong communication skills and ability to work in highly cross-functional teams
GREAT TO HAVES:
- Master's or PhD in Computer Science, Statistics, or related STEM fields (highly recommended)
- Previous experience with catalog quality, product attribute extraction, computer vision for e-commerce imagery, or search and discovery for two-sided platforms
- Experience building and validating LLM evaluation pipelines, including prompt iteration against labeled data and human-in-the-loop workflows
