Principal Engineer - Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning

Details

Airbnb is seeking a seasoned Principal AI/ML Researcher and Engineer with deep expertise in Bayesian Learning and Distributional Reinforcement Learning to lead 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). The role also involves innovating ways to interoperate and integrate Large Language Models (LLMs) and Large Multimodal Models (LMMs) with reasoning, planning, and decisioning abilities into Bayesian frameworks, and ensuring these models and supporting systems perform efficiently at scale and integrate into live systems that directly impact product and user experience.

Responsibilities

• Lead applied research in Bayesian systems, distributional reinforcement learning, and multi-modal architectures to advance AI and foundational intelligence for ranking, recommendations, and personalization.
• Bridge theoretical AI/ML advancements and real-world production systems; ensure research is applicable and scalable.
• Define and drive architecture of large-scale Bayesian framework–based AI systems.
• 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 designs.
• Innovate methods to interoperate with LLMs, LRMs, LMMs, and transformer-based architectures, using AI multi-agentic frameworks.
• Build and refine Bayesian or Markovian graph chains for uncertainty estimation, adaptive decision-making, and probabilistic reasoning.
• Develop foundational models by merging Bayesian techniques with classical ML and L[L/M/R]Ms and other advanced architectures.
• Continuously improve systems for scalability, performance, and robustness across diverse data sources and paradigms.
• Lead technical direction and strategy for AI/ML systems, influence cross-functional teams, perform code reviews, mentor engineers, and champion best practices.
• Work with structured and unstructured data to design models for diverse use cases; collaborate with partners to refine requirements and translate technical decisions into business value.
• Develop, productionize, and maintain scalable AI/ML pipelines (batch and real-time); implement advanced model evaluation (interpretability, hyperparameter optimization, drift detection); ensure system reliability through testing and validation.

Requirements

• Bachelor'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++, and expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch).
• Proven experience with Bayesian Neural Networks, Bayesian Learning, and Reinforcement Learning (including distributional RL).
• Strong math background in probability, statistics, and optimization.
• Experience 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 and designing knowledge-driven systems integrating external knowledge sources.
• Familiarity with foundational models, transformers, and their role interoperating with Bayesian systems.
• Exceptional leadership, collaboration, and communication skills in complex, matrixed organizations; track record of publishing research or developing novel AI/ML techniques.

Location & Work Eligibility

• This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager.
• You must live in a state where Airbnb, Inc. has a registered entity (some states excluded; check Airbnb careers for the up-to-date list).

Pay Range

• $296,000 — $370,000 USD (base pay range). This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Inclusion & Accommodation

• Airbnb is committed to inclusion and belonging and encourages all qualified individuals to apply.
• Applicants needing reasonable accommodation for the application/interview process can contact [email protected] with their full name, the role, and the accommodation requested.