About this role
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
About the Team
Klaviyo's AI & Analytics pillar builds the intelligence layer that helps marketers understand their customers, personalize every interaction, and prove the impact of their work. Two of our highest-leverage products live at the center of this: Product Recommendations and Audience Optimization. Both are ML-powered. Both exist for one reason: to help brands running autonomous marketing get a real, measurable lift in performance and revenue.
Klaviyo runs like an ecosystem of startups. Every team owns real outcomes, and the people who succeed here are builders who pull in the partners they need, even when those partners don't report to them. This role is a clear example of that model in action.
About the Role
We're looking for a Senior Product Manager to own the product and model strategy for two connected feature areas: Product Recommendations and Message Prioritization, with room to take on additional ML-powered feature pods as the portfolio grows.
Product Recommendations spans multiple model types, deep familiarity with product catalog data structures, and enterprise-grade customization: filters, guardrails, exclusions, and the business rules brands need layered on top of a model before they'll trust it in production.
Message prioritization decides who receives a message, which message they receive, and when. Any given profile might be eligible for several messages in a short window. This feature caps how many they actually get and picks the ones most likely to convert, so the model has to optimize for revenue and conversion at the same time it respects frequency limits.
Across both areas, this PM owns the full outcome: not just what ships, but whether it delivers positive lift for the brands using it. That means you're accountable for model performance the same way you're accountable for the product experience wrapped around it.
How You'll Make a Difference
• Own the roadmap for Product Recommendations, including model type selection, catalog data structure decisions, and enterprise-grade customization such as filters, guardrails, and exclusions
• Own the roadmap for Message Prioritization, defining how the model balances message frequency limits against conversion and revenue outcomes
• Define what model success looks like for each feature area and build the frameworks to measure lift, conversion improvement, and revenue impact over time
• Partner closely with ML modeling teams and softw