Staff Product Manager, Recommendations & Discovery

Who We Are

Babylist is the leading platform for expecting and new families. More than 10 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, guidance, and expert recommendations. As a modern, AI-forward tech company, Babylist has expanded from a universal registry into a full ecosystem — the Babylist Shop, Babylist Health, Babylist Money, NYC and LA showrooms, branded content, and more — generating $750M in revenue in 2025. Building the generational brand in baby, Babylist is reshaping the $235B kids and baby market and helping parents feel confident, connected, and cared for at every step.

Our Ways of Working

Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what’s possible and prove it through how they show up.

What the Role Is

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.

Who You Are

You are a demonstrated product leader who has spent meaningful time inside ML-powered consumer products. You have owned a recommendation, personalization, and/or discovery surface end-to-end at scale — and you have the scar tissue to prove it. You have held Senior PM, Staff PM, GPM, or comparable Lead roles. You’re motivated by the chance to bring what you’ve learned to a company that’s earlier in this journey than you’ve been before, and you see that as an asset, not a downgrade.

You bring:

• Real B2C ML product depth. You have shipped recommendations, search, ranking, or personalization systems in a consumer-facing product. You 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. You know the failure modes and the diligence required to ship ML responsibly.
• Real technical fluency with ML systems. You don’t write production model code, but you understand the full ML lifecycle — data pipelines, feature engineering, model training, deployment, monitoring, and iteration. You’re 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. You know that early ML investment is about getting the right reps on a small number of bets, not shipping breadth. You understand when a rule beats a model, when a model needs a guardrail, and when a hard-coded baseline is the right first step. You’d rather ship one excellent recommender and learn from it than launch six mediocre ones.
• Strategic foresight. You can articulate the maturity curve of personalization and discovery at Babylist — where we are, what’s next, and the effort behind each step. You hold a strong, opinionated view of the product and you know when to update your priors.
• Deep customer expertise. This is the irreplaceable PM contribution in a builder world, and it has to be a genuine strength. You talk to customers directly with regularity and bring concrete evidence (qualitative and quantitative) into every decision.
• Commercial ownership. You are fluent in the business. You understand how recommendations and feed surfaces drive registry completion, GMV, ad revenue, and retention. You can defend a unit economics model and partner with finance and data without needing them to translate.  You don’t celebrate launches — you own impact.
• Clarity of thought. You communicate with extreme clarity that moves conversations forward fast. You don’t mistake collaboration for consensus.
• AI-native daily practice. You actively use LLMs and AI coding tools to prototype, analyze, query data, and move faster than you could without them. You have intuition for what current models are good and bad at. This is table stakes at Babylist — every team uses AI daily — and we expect you to model what AI-native PM craft looks like for the team around you.
• Adaptability to change. You select for change, not against it. You jump in where needed, working across team boundaries without waiting for permission. You are humble, low-ego, and biased toward action.
• Strongly preferred: Background in e-commerce or marketplaces; experience helping build or scale an ML personalization function from scratch

How You Will Make An Impact

• 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.

About Compensation

We use a market-based approach to compensation. The starting salary range for this role is:

$214,057 to $256,885

Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity.

Why You Will Love Working At Babylist

Our Culture

• We work with focus and intention, then step away to recharge
• We believe in exceptional management and invest in tools and opportunities to connect with colleagues
• We build products that positively impact millions of people’s lives
• AI is intentionally embedded in how we work, create, and scale—supporting innovation and impact

Growth & Development

• Competitive pay and meaningful opportunities for career advancement
• We believe technology and data can solve hard problems
• We’re committed to career progression and performance-based advancement

Compensation & Benefits

• Competitive salary with equity and bonus opportunities
• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

Important Notices

Recorded Interviews. Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription.

Interview Integrity. AI is part of how we work at Babylist — we expect you to use it too. Your application and interviews should still reflect you and your own thinking. We’ll tell you when AI is encouraged. Misrepresentation at any stage may result in removal from consideration for this and future roles.

Connections at Babylist. If you have a family member or close personal relationship with a current Babylist employee, please let your recruiter know. This helps us keep our process fair and transparent for everyone.

Protect Yourself from Scams. All official outreach comes from the Babylist Talent Team via @babylist.com email addresses only. We will never ask for payment or personal financial information. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email — it’s not us. Verify open roles at babylist.com/careers.