Product Manager – Relevance and Personalization

📋 Description

• Define and lead the strategy for Airbnb's relevance and personalization platform, encompassing natural language query comprehension and multi-turn, context-sensitive discovery experiences.

• Make prioritization decisions that balance various competing objectives: guest satisfaction, host success, revenue generation, fairness, and the overall health of the marketplace.

• Collaborate with machine learning engineers and applied researchers to develop model strategies, evaluation frameworks, and experimental designs.

• Align cross-functional teams—Guest, Host, MarTech, Trust & Safety, and Customer Support—on common objectives and timelines.

• Propel the Tripcycle vision by ensuring the relevance and personalization layer integrates seamlessly across the entire trip lifecycle, from inspiration to post-trip experiences.

• Design and manage A/B experiments with meticulous metric design and long-term impact assessment.

• Convert intricate technical trade-offs into clear decisions for engineering teams and concise narratives for leadership.

• Cultivate an environment where engineers and product managers work together to shape future innovations.

• Stay attuned to guest and host needs by synthesizing user research, marketplace analytics, and competitive insights to enhance intuition and refine strategic direction.

⛳️ Requirements

• Over 10 years of product management experience, including a minimum of 3 years focused on machine learning, search, recommendations, or AI-driven products at scale.

• Proven history of owning the strategy and roadmap for technically intricate systems—going beyond feature management to set direction and make challenging prioritization decisions.

• Strong proficiency in experimentation: comfortable designing A/B tests, analyzing counterfactual results, and considering proxy metrics in relation to long-term outcomes.

• Experience in working with two-sided marketplaces or platforms where supply-side and demand-side trade-offs were effectively balanced.

• Ability to earn the respect of Staff and Principal-level engineers and researchers—you may not need to code, but you must engage at a level that fosters credibility.

• Clear and structured communicator, capable of simplifying complex technical trade-offs for executives and translating strategic goals into actionable guidance for engineering teams.

• Experience with production-level LLM-based products, particularly those that involve evaluation challenges, latency considerations, or safety and guardrail measures (preferred).

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

• Background in collaborating with applied researchers or teams that publish findings externally (preferred).

🏝️ Benefits

• Bonus

• Equity

• Employee Travel Credits