Staff Machine Learning Engineer

Join Babylist, a leading parenting resource, as a Staff Machine Learning Engineer. In this role, you will own recommendations and personalization across Babylist's consumer experience, including the homepage feed, product recommendations, search, and the ML-powered systems that make registry building effortless. You will set the technical direction for personalization, work alongside a PM, Engineering Manager, Senior MLE, and fullstack software engineers, and shape the future of Babylist's personalization efforts.

Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend

An ability to take an ambiguous problem and start moving before anyone hands you the full picture

About Babylist

• AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next
• You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey

Responsibilities

• Assumer la responsabilité de la direction technique des modèles de personnalisation et de recommandation, en définissant la stratégie et la feuille de route pour l'évolution des modèles.
• Collaborer avec les équipes produit, design et données pour identifier les opportunités d'amélioration des systèmes de recommandation et de personnalisation, et pour définir les priorités de développement.
• Encadrer et coacher les ingénieurs de l'équipe, en partageant votre expertise en apprentissage automatique et en contribuant à l'amélioration continue des pratiques de l'équipe.
• You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work
• Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias

Requirements

• An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue
• A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings

Pay

USD 233,500 - 348,840