Staff Product Manager, Babylist
Recommendations & Discovery
$214.1-256.9k
+ target 20% annual bonus and competitive equity.
Senior and Expert level
Remote from US
Online universal baby registry
Open for applications
Online universal baby registry
1001+ employees
B2CMarketplaceConsumer GoodseCommerce
Open for applications
$214.1-256.9k
+ target 20% annual bonus and competitive equity.
Senior and Expert level
Remote from US
1001+ employees
B2CMarketplaceConsumer GoodseCommerce
Company mission
To help expecting parents get exactly what they need for the arrival of their new baby.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Since its 2011 launch, Babylist has grown into one of the most highly rated baby registries in the US. The difference it offers is that it allows users to include products from any store in their registries. On top of this, the company’s model also focuses heavily on creating informational content, which allows it to generate ad revenue while building customer loyalty.
Originally scaled with fairly low venture funding, Babylist claims half of new parents in the US now use its services. This, given that the baby products industry is worth close to $90 billion, shows the company's immense growth and speaks to the impact it has made in the space.
Babylist has seen strong funding in the past, which has fuelled projects such as the launch of virtual showrooms and further expanded the company's presence. The company acquired Expectful, a health and wellness tool, in 2023 with the long-term vision of combining the two companies into a larger health and wellness media property that can help people navigate all aspects of parenthood from fertility to diapers.
Steph
Company Specialist at Welcome to the Jungle
Insights
Led by a woman
Top investors
67% employee growth in 12 months
Company
Funding (1 round)
Nov 2021
$40m
SERIES C
Total funding: $40m
Company benefits
- HAPPIER WEEKENDS – We work to live, not live to work. That means we generally don’t work nights or weekends, and we offer 10 paid holidays throughout the year, in addition to your paid time off.
- PAID TIME OFF THAT WORKS FOR YOU – Life is unpredictable. Use your time off for what you need, whether that’s a vacation, family event or a day to unplug.
- PARENTAL LEAVE – We offer a flexible, 12-week paid parental leave policy.
- FLEXIBLE BENEFITS – Choose from benefits that support your working style, whether that's remote, in the office or something in between.
- HEALTH & WELLNESS – Wellness benefits include 100% paid coverage for medical, vision and dental for full-time employees.
- BABYLIST STORE DISCOUNT – All full-time employees receive a generous Babylist Store discount.
Company HQ
Emeryville, CA
Leadership
Natalie Gordon
(Founder & CEO)Former Software Engineer at Amazon. Initially founded Babylist as a side project and has since taken the company to a market leading status.
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