Senior Staff Applied ML/AI Scientist (Search)

Join Faire, a fast-growing online wholesale marketplace, as a Staff Applied ML/AI Scientist. In this role, you will drive the technical vision and ML algorithm strategy for the Search Group, leading the advancement of real-time search and recommendation systems. You will own the next-generation search engine, design and productionize natural language search and discovery systems, and mentor a team of talented scientists and engineers. This is a unique opportunity to work at the forefront of algorithms and make a significant impact on customer value and company growth.

• Conduire la vision technique, la stratégie des algorithmes ML et la conception du système pour les systèmes de recherche et de recommandation en temps réel.
• Diriger le développement de modèles et les efforts de déploiement basés sur GPU, en utilisant des frameworks comme Triton pour évoluer l'inférence de manière fiable et efficace.
• Mentorer et développer des scientifiques appliqués seniors et des ingénieurs en apprentissage automatique, et établir des meilleures pratiques autour du développement de modèles.
• A strong track record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization
• Excellent communication and cross-functional influence—you raise the technical bar beyond your immediate team
• Hands-on experience with deep learning libraries (e.g. PyTorch) and vector search infrastructure (e.g. Faiss, ScaNN, Pinecone)
• 7+ years of experience building large-scale ML systems, including 3+ years in search, recommendation, or ads ranking
• Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments
• A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production
• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI
• MS or PhD in Computer Science, Statistics, or a related STEM field
• Strong practices around model development, agent workflow evaluation, and MLOps