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 seasoned Principal AI/ML Researcher and Engineer with deep expertise in Bayesian Learning, and Distributional

Reinforcement Learning (RL) to lead the advanced research and development of cutting-edge intelligence AI models. These systems

will integrate foundational Bayesian frameworks with advanced architectures, including Mixture of Models, multi-pass sharded

systems, multitask and multi-objective optimization, and external knowledge incorporation. Additionally, the role involves

innovating ways to interoperate and integrate Large Language Models (LLMs) and Large Multimodal Models (LMMs) with Reasoning,

Planning, and Decisioning abilities into the Bayesian frameworks to create a seamless foundational model fabric that synergizes

with diverse model ecosystems.The role will require ensuring these models and supporting systems perform efficiently at scale,

integrating them into live systems that directly impact product and user experience.

Our goal is to build next-generation AI platforms that redefine personalization, decision-making, and intelligence across diverse

applications. You will work on developing production-level systems, collaborate with cross-functional teams, and play a pivotal

role in shaping our AI/ML strategy.

RELEVANCE AND IMPACT OF THIS ROLE

This role drives Airbnb's evolution toward probabilistic, uncertainty-aware intelligence systems capable of reasoning under

ambiguity and learning continuously from dynamic environments. The near-term impact spans improved personalization quality,

ranking quality, uncertainty estimation, and adaptive decision-making across guest and host experiences — enabling policy-driven

intelligence that handles long-tail discovery, evolving preferences, and complex marketplace dynamics.

Longer term, this role helps establish Airbnb's leadership in adaptive probabilistic intelligence by building the foundational

substrate that connects Bayesian learning, reinforcement learning, foundational models, multi-agent orchestration, and large-scale

personalization into a unified adaptive architecture — where AI systems continuously balance exploration, exploitation,

uncertainty, and ecosystem optimization at scale.

WHAT YOU WILL DO

RESEARCH & INNOVATION:

Lead groundbreaking applied research in Bayesian systems, distributional reinforcement learning, and multi-modal architectures

to drive novel advances in AI and Foundational Intelligence (Ranking, Recommendations, Personalization) to fill out gaps in the

Long Tail Curve of Discovery in order to grow the Business Offerings on both Guest and Host Long Tail Ends

Bridge the gap between theoretical AI/ML advancements and real-world production systems
Ensure that new research can be effectively applied and scaled to meet practical needs.

ARCHITECT AND DESIGN:

Define and drive the architecture of large-scale Bayesian Framework-based AI systems at Airbnb.
Develop multi-pass sharded Bayesian + Discriminative/Generative single to multi agent systems for scale and efficiency.
Incorporate Mixture of Models and Agents, multitask learning, multi-objective optimization, and external knowledge systems into

model designs.

Innovate methods to interoperate with LLMs, LRMs, LMMs, and transformer-based architectures, ensuring seamless integration and

collaboration within the AI ecosystem using AI Multi-Agentic Frameworks.

MODEL DEVELOPMENT:

Build and refine Bayesian or Markovian Graph chains to incorporate uncertainty estimation, adaptive decision-making, and

probabilistic reasoning.

Develop foundational models by merging Bayesian techniques with Classical ML with L[L/M/R]Ms and other advanced architectures,

ensuring compatibility and synergy.

Continuously improve systems for scalability, performance, and robustness, enabling models to absorb and adapt to diverse data

sources and paradigms.

TECHNICAL LEADERSHIP:

Lead technical direction and strategy for AI/ML systems.
Influence cross-functional teams, including engineering leaders, product managers, and data scientists, to adopt unified

intelligence platform approaches.

Perform code reviews, mentor engineers, and champion best practices in AI/ML.

COLLABORATION:

Work with structured and unstructured data to design models for diverse use cases.
Collaborate with cross-functional partners to identify opportunities, refine requirements, and drive impactful solutions.
Translate complex technical decisions into business value.

OPERATIONAL EXCELLENCE:

Develop, productionize, and maintain scalable AI/ML pipelines, including batch and real-time use cases.
Implement advanced model evaluation systems, including interpretability, hyperparameter optimization, and drift detection.
Ensure system reliability and performance through rigorous testing and validation.

MINIMUM QUALIFICATIONS

Master's degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
15+ years of technical experience in Applied Machine Learning, including producing code and deploying production systems.
Strong programming skills in Python, Scala, Java, or C++, with expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch).
Proven experience with Bayesian Neural Networks, Bayesian Learning, and Reinforcement Learning.
Strong math background in probability, statistics, and optimization.
Experience with building scalable AI/ML systems using technologies like Spark, Kafka, and distributed architectures.
Familiarity with advanced ML techniques, including Mixture of Models, Ensemble Techniques, multitask learning, and sharded

architectures.

PREFERRED QUALIFICATIONS

Ph.D. in a relevant technical field with 15+ years of experience in AI/ML research and engineering.
Expertise in architecting and leading large-scale AI/ML systems with enterprise-level impact.
Hands-on experience with multitask and multi-objective optimization systems.
Experience in designing knowledge-driven systems and integrating external knowledge sources.
Familiarity with foundational models, transformers, and their role in interoperating with Bayesian systems.
Exceptional leadership, collaboration, and communication skills in complex, matrixed organizations.
Strong track record of publishing research or developing novel AI/ML techniques.

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as

agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered

entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if

the state you live in is on the exclusion list . If your position is employed by another Airbnb entity, your recruiter will inform

you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement,

and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals

are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and

require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com.

Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting

process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online

application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training,

transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be

modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range

$296,000—$370,000 USD

Role

Principal AI/ML Researcher / Engineer In Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning

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