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

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

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 advances Airbnb's AI capabilities toward reasoning, planning, and adaptive decision-making across complex real-world environments. The near-term impact spans improved decision quality, contextual intelligence, adaptive personalization, and operational coordination across guest and host workflows — introducing goal-directed reasoning systems capable of handling ambiguity, constraints, trade-offs, and multi-step planning. Guests benefit from more intelligent planning and assistance, while hosts and internal teams gain systems capable of adaptive optimization, dynamic recommendations, policy-aware decisioning, and intelligent workflow orchestration.

Longer term, this role helps establish Airbnb's leadership in cognitive AI systems and distributed intelligence architectures. The technologies developed here become the decisioning and reasoning substrate underlying the broader ecosystem — enabling AI systems that can deliberate, coordinate, adapt, and make coherent long-horizon decisions across multiple agents and environments. Over time, this positions Airbnb as an intelligent coordi