Senior Applied AI/ML Scientist (Search Ranking)

Join Faire, a leading e-commerce platform, as a Senior Applied AI/ML Scientist. In this role, you will shape the technical vision and machine-learning algorithm strategy for our search ranking system. You will work at the forefront of algorithms, combining various techniques to deliver personalized product recommendations. This is a unique opportunity to influence the personalized discovery experience at Faire while collaborating with a talented team of scientists and engineers.

- Concevoir et mettre en œuvre des algorithmes de classement de recherche de nouvelle génération en intégrant les dernières avancées en apprentissage profond et en apprentissage automatique. - Collaborer étroitement avec les équipes de l'entreprise pour expérimenter et améliorer les modèles d'apprentissage automatique pour le classement de recherche et au-delà. - Partager les meilleures pratiques concernant le développement de modèles d'apprentissage profond, l'évaluation des flux de travail des agents et MLOps.

- Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark) - Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains - A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production - A Master’s or PhD in Computer Science, Statistics, or a related STEM field - Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team - 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking - Contributions to open-source ML libraries or peer-reviewed publications in ML/AI - Industry experience developing and productizing LLM-based applications and systems in the search domain - Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces - Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity - Familiarity with Kotlin