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

9 minutes ago
United States
Full-time
Lead
AI (Artificial Intelligence)
Software Development
C++ Java LLM Python PyTorch Reinforcement Learning
Apply Now
Airbnb

Airbnb

Airbnb is the world's largest community-driven hospitality company, offering homes and experiences in 191 countries. It is an online marketplace connecting people to unique accommodations and experiences globally.

Hotels, Restaurants & Leisure
5K-10K
Founded 2008
View All Jobs 142

Description

  • Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale.
  • Advance LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents.
  • Design methods for plan induction, value estimation, and contingency modeling within intelligent agents.
  • Explore and validate protocols for distributed reasoning and joint planning among cooperative agents.
  • Architect systems that integrate post-trained LLMs/LRMs, graph-structured memory, and RL-driven controllers.
  • Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers.
  • Define communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms for multi-agent systems.
  • Build and evolve stateful models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol grounding.
  • Set direction for planning and reasoning infrastructure within the AI/ML platform strategy.
  • Work across product, infrastructure, design, researchers, ontologists, and ML engineers to translate ambiguous product intent into multi-stage reasoning pipelines.
  • Productionize real-time reasoning loops with low-latency inference, caching, retrieval-augmented generation, and streaming updates to symbolic memory.
  • Create monitoring, attribution, and evaluation pipelines for agent behavior and decision quality.

Requirements

  • Master’s degree or equivalent in Computer Science, AI, Cognitive Science, or a related field.
  • Recent published work or patents in AI, Cognitive Science, or related fields.
  • 15+ years of experience in AI/ML, including post-training architectures and production-scale reasoning systems.
  • Advanced coding proficiency in Java, Python, C++, or similar languages.
  • Experience with ML/RL frameworks such as PyTorch, Ray, JAX, or RLlib at scale.
  • Proven experience integrating LLMs/LRMs with Knowledge Graphs or structured world models.
  • Deep understanding of Reinforcement Learning and its application to decisioning and planning.
  • Fluency in hybrid model architectures such as connectionist-symbolic fusion, retrieval-based agents, or goal-directed transformers.
  • Experience working on multi-agent coordination, distributed RL, or cooperative inference systems.
  • Ph.D. in AI, Machine Learning, Robotics, Cognitive Systems, or a related area preferred.
  • Published work or patents in multi-agent reasoning, plan synthesis, knowledge-augmented learning, or generative control preferred.
  • Experience with cognitive architectures, neuro-symbolic systems, or agent-based simulation environments preferred.
  • Demonstrated ability to lead cross-functional research-to-production transitions preferred.
  • Experience with memory architectures, task graphs, or semantic program induction preferred.
  • Prior work on distributed intelligence platforms with explicit agent interaction models and collective decision-making logic preferred.
  • Must live in a state where Airbnb, Inc. has a registered entity for this US-remote-eligible role.

Benefits

  • Base pay range of $296,000 to $370,000 USD.
  • Eligible for bonus compensation.
  • Eligible for equity.
  • Eligible for benefits.
  • Eligible for Employee Travel Credits.
  • US-remote-eligible with occasional office or offsite attendance as agreed with the manager.
  • Reasonable accommodations are available for candidates with disabilities during the application and interview process.

Interested in this position?

Apply directly on the company website

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