Staff Product Manager, Recommendations & Discovery

Babylist is a leading platform for expecting and new families, and they are seeking a Staff Product Manager to lead personalization and discovery across their consumer experience. This role will involve owning the strategy, quality, and impact of recommendations and discovery systems while collaborating closely with the ML Engineering team.

Responsibilities:

• Own recommendations and discovery at Babylist end-to-end. Strategy, KPIs, quality bar, impact, the hard tradeoffs. You are the person the rest of the company looks to when a question about discovery or recommendations has to get answered
• Set the one-year horizon for product personalization at Babylist. Articulate where we should be a year from now, defend the sequence of bets that gets us there, and update with conviction and speed when evidence demands
• Be a true peer to the ML EM. Set technical and product direction together. Help shape the modeling, data, and evaluation infrastructure that makes the next five years of work possible. Translate ambiguous business problems into clear technical direction the ML team can act on
• Set the quality bar for ML-powered experiences. Decide what 'good' looks like for a recommendation, and what unacceptable looks like. Make the hard tradeoffs
• Raise the whole company's judgment about ML investment. As the company’s definitive voice on ML and recommendations, you'll help leadership develop intuition for where ML compounds — what's table stakes, what's a real lever, and what to avoid. You will make the case for where ML matters and build belief that gets the right bets funded
• Operate as a AI-enabled builder. Use AI-native workflows in your own work. Stand up prototypes, run your own analyses, and ship things yourself when that's the fastest path to the right answer
• Mentor and develop the PMs around you. Help raise the bar for the function. Give specific, timely feedback that improves the team's output. Contribute to hiring as the org evolves

Requirements:

• Demonstrated product leader with meaningful time inside ML-powered consumer products
• Owned a recommendation, personalization, and/or discovery surface end-to-end at scale
• Held Senior PM, Staff PM, GPM, or comparable Lead roles
• Real B2C ML product depth
• Shipped recommendations, search, ranking, or personalization systems in a consumer-facing product
• Fluent in candidate generation vs. ranking, online vs. offline evaluation, cold start, exploration vs. exploitation, novelty effects, and tradeoffs between business objectives and user-perceived relevance
• Real technical fluency with ML systems
• Understand the full ML lifecycle — data pipelines, feature engineering, model training, deployment, monitoring, and iteration
• Comfortable reading a model design doc and pushing back on architectural choices
• Builder's instinct for early-stage ML
• Strategic foresight regarding the maturity curve of personalization and discovery
• Deep customer expertise
• Commercial ownership and understanding of how recommendations and feed surfaces drive registry completion, GMV, ad revenue, and retention
• Clarity of thought and ability to communicate with extreme clarity
• AI-native daily practice using LLMs and AI coding tools
• Adaptability to change and ability to work across team boundaries
• Background in e-commerce or marketplaces
• Experience helping build or scale an ML personalization function from scratch