Product Manager, Relevance and Personalization

Airbnb
San Francisco, CA, USA2026-05-07

About the job

As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale.

Responsibilities

Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences

Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health

Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design

Align cross-functional partners — Guest, Host, MarTech, Trust & Safety, Customer Support — on shared goals and sequencing

Drive the Tripcycle vision: ensuring R&P's intelligence layer connects across the full trip lifecycle, from inspiration through post-trip

Design and oversee A/B experiments with rigorous metric design and long-term effect measurement

Translate complex technical tradeoffs into clear decisions for engineering teams and concise narratives for leadership

Foster an environment where engineers and product managers collaborate on building the future

Stay close to guests and hosts: synthesize user research, marketplace data, and competitive signals to sharpen your intuition and refine strategy

Qualifications

Minimum

10+ years of product management experience, with at least 3 years on ML, search, recommendations, or AI-powered products at scale

Track record of owning strategy and roadmap for technically complex systems — not just managing features, but setting direction and making hard prioritization calls

Strong experimentation fluency: comfortable designing A/B tests, interpreting counterfactual results, and reasoning about proxy metrics vs. long-term outcomes

Experience working on two-sided marketplaces or platforms where you balanced supply-side and demand-side tradeoffs

Ability to earn the respect of Staff and Principal-level engineers and researchers — you don't need to write code, but you need to engage at a level that builds credibility

Clear, structured communicator who can distill complex technical tradeoffs for executives and translate strategic intent into actionable guidance for engineers

Preferred

Experience with LLM-based products in production — ideally involving evaluation challenges, latency constraints, or safety and guardrail work (preferred)

Familiarity with reinforcement learning, contextual bandits, or explore/exploit frameworks in a product context (preferred)

Background working alongside applied researchers or with teams that publish externally (preferred)