Staff Product Manager, Recommendations & Discovery

Babylist

23h • Remote

About The Position

We're hiring a Staff Product Manager to own personalization and discovery across Babylist's consumer experience — the homepage feed, product recommendations, and the ML-powered systems that make the registry building journey feel effortless. Babylist was built on editorial recommendations — products chosen by humans with deep baby gear expertise – which are an important part of the foundation of the trust we've earned with millions of families. We now have the remit to build on our editorial strength; using one of the richest first-party datasets in parenting to layer personalized, ML-powered recommendations across every consumer decision point. We are early on the journey, have a real mandate, and need a product leader who has seen ML personalization done at scale to come define what great looks like for Babylist.

If you're looking to step into a mature ML organization and optimize on the margins, this isn't the right role. If you've worked inside a strong ML personalization team, learned what good looks like, and want to bring that knowledge to a company early on in this journey — with the leverage to shape what we build and how we build it — read on.

Registry building is the heart of the Babylist product — every parent builds a list of dozens of products, from stroller to swaddle, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). That makes registry building one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, and a user who genuinely wants help. We're only beginning to build on that opportunity.

This role is the authority on recommendations and discovery at Babylist. You hold the quality bar, set the one-year horizon, and operate as the foremost expert on the space inside the company. You shape how the whole company thinks about personalization. You partner closely with our ML Engineering team — opinionated about model behavior, fluent in tradeoffs between business goals and user value, and able to hold real conversations about retrieval, ranking, candidate generation, and evaluation.

Requirements

• Demonstrated product leader who has spent 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.
• Can speak fluently about candidate generation vs. ranking, online vs. offline evaluation, cold start, exploration vs. exploitation, novelty effects, and the tradeoffs between business objectives and user-perceived relevance.
• Know the failure modes and the diligence required to ship ML responsibly.
• 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, pushing back on architectural choices when the product reality demands it, and being a true peer to a senior ML EM rather than a translator.
• A builder's instinct for early-stage ML. Knows that early ML investment is about getting the right reps on a small number of bets, not shipping breadth.
• Understands when a rule beats a model, when a model needs a guardrail, and when a hard-coded baseline is the right first step.
• Strategic foresight. Can articulate the maturity curve of personalization and discovery at Babylist — where we are, what's next, and the effort behind each step.
• Holds a strong, opinionated view of the product and knows when to update priors.
• Deep customer expertise. Talks to customers directly with regularity and brings concrete evidence (qualitative and quantitative) into every decision.
• Commercial ownership. Fluent in the business. Understands how recommendations and feed surfaces drive registry completion, GMV, ad revenue, and retention.
• Can defend a unit economics model and partner with finance and data without needing them to translate.
• Clarity of thought. Communicates with extreme clarity that moves conversations forward fast.
• AI-native daily practice. Actively uses LLMs and AI coding tools to prototype, analyze, query data, and move faster than could without them.
• Adaptability to change. Jumps in where needed, working across team boundaries without waiting for permission.
• Humble, low-ego, and biased toward action.

Nice To Haves

• Background in e-commerce or marketplaces
• Experience helping build or scale an ML personalization function from scratch

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.

Benefits

• Competitive pay and meaningful opportunities for career advancement
• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Winter Wonder Week: the whole company takes a paid week off at the end of the year, whether or not you celebrate anything, so everyone's out at once and comes back refreshed
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed