Own the direction and implementation of Babylist’s personalization domain, including recommendation, search, feed models, custom embeddings, and shared representations. Take ambiguous problems from concept through production, owning architecture, deployment, monitoring, retraining, evaluation, and customer impact. Partner with product, design, and data, establish AI development standards, make cross-team technical decisions, and coach senior engineers while remaining hands-on with complex machine learning systems.

Lead product for personalization and discovery across Babylist: own strategy, KPIs, and quality for recommendations and feed surfaces. Partner with ML engineering on retrieval, ranking, candidate generation, and evaluation. Drive one-year roadmap, commercial impact, AI-native prototyping, and mentor PMs while raising company-wide judgment on ML investment and implementation.