Airbnb
5001 - 10000 employees
Founded 2007
👥 B2C
🛍️ eCommerce
💰 Post-IPO Equity on 2020-12
B2C • eCommerce • Hospitality
Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.
Principal AI/ML Researcher – Reasoning, Planning, Decision-making Systems
🕒 June 1
🇺🇸 United States – Remote
💵 $296k - $370k / year
⏰ Full Time
🔴 Lead
🧠 AI Research Scientist
🦅 H1B Visa Sponsor
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Airbnb
5001 - 10000 employees
Founded 2007
👥 B2C
🛍️ eCommerce
💰 Post-IPO Equity on 2020-12
B2C • eCommerce • Hospitality
Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.
📋 Description
• Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale. • Advance techniques in 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 in multi-agent systems. • Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers. • Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates. • Ensure modularity and extensibility through multi-agent frameworks, agentic substrates, and declarative planning pipelines. • Define communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms to foster emergent cooperative intelligence.
🎯 Requirements
• Masters or equivalent in Computer Science, AI, Cognitive Science, or related fields. • Recent published work or patents in AI, Cognitive Science, or related fields. • 15+ years in AI/ML, including post-training architectures and production-scale reasoning systems. • Advanced coding proficiency in Java, Python, C++, or similar, with experience in ML/RL frameworks (e.g., PyTorch, Ray, JAX, 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: connectionist-symbolic fusion, retrieval-based agents, or goal-directed transformers. • Experience working on multi-agent coordination, distributed RL, or cooperative inference systems.
🏖️ Benefits
• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
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