Senior Engineering Manager, Machine Learning

Babylist is the leading registry, e-commerce, and content platform for growing families. As Babylist’s Senior Engineering Manager, Machine Learning & Discovery+Site Monetization, you’ll lead the team driving the next era of our machine learning and personalization efforts across the product.

Responsibilities:

• Build and lead the ML & personalization function: Hire, mentor, and support a multidisciplinary team (Machine Learning Engineers, Software Engineers, Product Manager, and occasional Designer), shaping the roadmap, standards, and culture for ML at Babylist
• Own high-impact ML initiatives: Deliver personalization systems that improve discovery, engagement, and monetization across key surfaces, directly impacting business outcomes
• Set technical and algorithmic direction: Define modeling approaches, data strategy, and system architecture in partnership with senior technical leaders, balancing experimentation with scalable execution
• Be hands-on when needed: Review ML/DS designs and code, build proof-of-concept models, and conduct your own data science research to de-risk ideas and accelerate progress
• Develop talent: Coach engineers on technical growth, career progression, and performance, combining strong technical standards with empowerment
• Drive cross-functional alignment: Partner closely with Product, Design, Analytics Engineering, and Data to translate ambiguous business problems into clear technical direction
• Understand the full funnel: Develop a deep understanding of Babylist’s user journeys, user feedback loops, and financial models — and how ML systems influence them end-to-end

Requirements:

• 3+ years of experience as a front-line manager delivering production-grade software or ML systems
• 5+ years of experience as an individual contributor in ML or Data Science, plus proven experience leading teams that build end-to-end machine learning systems, ideally in personalization, recommendations, or consumer-facing ML products
• Deep familiarity with the Python ML ecosystem (e.g., pandas, sklearn, xgboost, PyTorch) and comfortable reviewing designs, unblocking technical challenges, and setting high technical standards
• Experience supervising ML Engineers and/or Data Scientists; bonus points for experience managing Software Engineers
• Strong understanding of the full ML lifecycle, including data pipelines, workflow orchestration (e.g., Airflow), deployment, monitoring, and iteration in production
• Product-minded: passionate about technology, but primarily motivated by solving real user problems and driving business impact
• Experience working with large-scale, real-time or near-real-time data systems
• Comfortable owning and evolving the ML tech stack end-to-end, from data and modeling through production systems
• Background in consumer-facing products; experience in e-commerce, marketplaces, or complex user journeys is strongly preferred
• You're comfortable and enthusiastic about working in an AI-forward environment where AI tools are part of daily operations