Principal AI/ML Researcher / Engineer Reasoning, Planning, and Decision-making systems

About the role

We are seeking a Principal / Distinguished AI/ML Researcher and/or Engineer with deep experience in reasoning, planning, and decision-making systems. This role is ideal for individuals who have architected post-training intelligence frameworks, integrated Large Reasoning Models (LRMs) with Knowledge Graphs, and applied Reinforcement Learning (RL) as a first-class component of adaptive planning and control. You will be responsible for inventing, scaling, and operationalizing intelligent decisioning substrates that blend symbolic and sub-symbolic methods, enabling next-generation AI systems that go beyond pattern recognition into the realm of deliberation, foresight, and agency. Our mission is to build cognitive AI systems that combine post-trained foundational models, explicit memory and knowledge, and recursive planning strategies to power sophisticated real-world decisioning in personalized environments. You will collaborate across disciplines and influence company-wide AI architecture. A core dimension of this role is the design and deployment of multi-agent systems, where reasoning, planning, and decisioning are distributed across networks of intelligent agents. You will formulate coherent, synergistic strategies that enable agents to cooperate, negotiate, and align objectives, ensuring that distributed intelligence converges to purposeful, high-quality outcomes across contexts. Relevance and Impact of This Role This role has the potential to fundamentally transform Airbnb from a platform that primarily predicts and ranks into a platform capable of reasoning, planning, and making adaptive decisions across complex real-world environments. In the short term, the impact comes from improving decision quality, contextual intelligence, adaptive personalization, and operational coordination across guest and host workflows. AI systems would move beyond static prediction and retrieval toward goal-directed reasoning systems capable of handling ambiguity, constraints, trade-offs, and multi-step planning. Guests would experience more intelligent planning, coordination, and conversational assistance, while hosts and internal teams would benefit from systems capable of adaptive optimization, dynamic recommendations, policy-aware decisioning, and intelligent workflow orchestration. Internally, these systems would significantly improve search, ranking, personalization, support, experimentation, and operational automation by introducing reasoning-aware and planning-aware intelligence into the AI stack. In the medium term, Airbnb could evolve into a deeply adaptive cognitive marketplace platform where AI systems continuously reason about goals, constraints, user intent, marketplace dynamics, and long-term outcomes. Instead of isolated models making narrow predictions, the platform would increasingly operate through reasoning and planning substrates that coordinate retrieval, memory, reinforcement learning, knowledge graphs, and multi-agent orchestration into unified decision-making systems. Airbnb would gain the ability to support complex multi-stage planning and adaptive coordination across travel, hosting, operations, support, trust, and marketplace optimization. This would create stronger ecosystem intelligence, operational leverage, adaptive personalization, and marketplace resilience while enabling the platform to handle increasingly sophisticated and dynamic real-world interactions. In the long term, this role helps establish Airbnb's strategic leadership in cognitive AI systems and distributed intelligence architectures. The technologies developed under this role become the decisioning and reasoning substrate underlying the entire ecosystem - enabling AI systems that can deliberate, coordinate, adapt, simulate outcomes, reason under uncertainty, and make coherent long-horizon decisions across multiple agents and environments. Airbnb would evolve beyond a recommendation and transaction platform into an intelligent coordination and planning ecosystem capable of operating as a large-scale real-world cognitive system. Over time, this could position Airbnb as one of the most advanced applied reasoning and multi-agent intelligence platforms in the consumer internet - where AI systems do not merely predict behavior, but actively reason, plan, and coordinate actions across the marketplace in ways that continuously improve user outcomes, ecosystem health, and long-term strategic adaptability.