[Remote] Principal AI/ML Researcher / Engineer In Reasoning, Planning, and Decision-making systems

Note: The job is a remote job and is open to candidates in USA. Airbnb is a global company that connects hosts and guests through unique stays and experiences. They are seeking a Principal AI/ML Researcher/Engineer to develop cognitive AI systems that enhance reasoning, planning, and decision-making capabilities, collaborating across disciplines to improve decision quality and operational coordination.ResponsibilitiesDrive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale in order to incorporate genAI into the ranking / recommendation / personalization stack in both single model to multi-agent ( system ) level intelligence with objective to grow the business (new user growth, abandoned user, long tailed user) in existing and new business areas while supporting Multi-Modal NL → Conversational InterfacesAdvance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agentsDesign methods for plan induction, value estimation, and contingency modeling within intelligent agentsExplore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systemsArchitect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllersDesign recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substratesEnsure modularity and extensibility through multi-agent frameworks, agentic substrates, and declarative planning pipelinesDefine communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms to foster emergent cooperative intelligenceBuild and evolve stateful, dynamic models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol groundingImplement hybrid pipelines that couple learned embeddings, prompted generative models, and graph-theoretic inferenceOptimize systems for adaptive exploration, planning horizon control, and policy robustnessDevelop frameworks for distributed value propagation, multi-agent credit assignment, and global planning from local agentsSet direction for planning/reasoning infrastructure within the AI/ML platform strategyServe as the technical conscience and architectural leader across high-stakes AI initiatives involving autonomous agents or high-fidelity decision pipelinesMentor teams in systems thinking, causal modeling, symbolic-connectionist integrations, and long-term planning under uncertaintyLead development of multi-agent reasoning systems, defining principles for inter-agent knowledge exchange, goal delegation, and cooperative decision resolutionWork across disciplines—product, infra, and design—to translate ambiguous product intent into multi-stage reasoning pipelinesPartner with researchers, ontologists, and ML engineers to encode world knowledge, goals, and values into usable inference artifactsContribute to a company-wide understanding of what it means to make intelligent choices, not just predictionsCollaborate with internal teams on distributed agent coordination, shared memory protocols, and policy harmonization across decision surfacesProductionize real-time reasoning loops with low-latency inference, caching, retrieval-augmented generation, and streaming updates to symbolic memoryDeploy post-training hooks for inserting logic, constraints, and domain priors into existing large modelsCreate advanced monitoring, attribution, and evaluation pipelines for agent behavior and decision qualityOperationalize multi-agent orchestration, ensuring reliable and fault-tolerant communication and decision propagationSkillsMasters or equivalent in Computer Science, AI, Cognitive Science, or related fieldsRecent published work or patents in AI, Cognitive Science, or related fields15+ years in AI/ML, including post-training architectures and production-scale reasoning systemsAdvanced coding proficiency in Java, Python, C++, or similar, with experience in ML/RL frameworks (e.g., PyTorch, Ray, JAX, RLlib) at scaleProven experience integrating LLMs/LRMs with Knowledge Graphs or structured world modelsDeep understanding of Reinforcement Learning and its application to decisioning and planningFluency in hybrid model architectures: connectionist-symbolic fusion, retrieval-based agents, or goal-directed transformersExperience working on multi-agent coordination, distributed RL, or cooperative inference systemsPh.D. in AI, Machine Learning, Robotics, Cognitive Systems, or related areasPublished work or patents in multi-agent reasoning, plan synthesis, knowledge-augmented learning, or generative controlExperience in cognitive architectures, neuro-symbolic systems, or agent-based simulation environmentsDemonstrated ability to lead cross-functional research-to-production transitionsExperience with memory architectures, task graphs, or semantic program inductionPrior work on distributed intelligence platforms with explicit agent interaction models and collective decision-making logicBenefitsBonusEquityBenefitsEmployee Travel CreditsCompany OverviewAirbnb is an online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet. It was founded in 2008, and is headquartered in San Francisco, California, USA, with a workforce of 5001-10000 employees. Its website is https://www.airbnb.com.Company H1B SponsorshipAirbnb has a track record of offering H1B sponsorships, with 27 in 2026, 234 in 2025, 176 in 2024, 160 in 2023, 270 in 2022, 250 in 2021, 274 in 2020. Please note that this does not guarantee sponsorship for this specific role.