Product Manager, Relevance and Personalization

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

Requirements

• 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

Nice-to-Haves

• Experience with LLM-based products in production — ideally involving evaluation challenges, latency constraints, or safety and guardrail work
• Familiarity with reinforcement learning, contextual bandits, or explore/exploit frameworks in a product context
• Background working alongside applied researchers or with teams that publish externally

Compensation

Pay Range: $232,000—$282,000 USD (base pay). Role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.