Principal AI/ML Researcher / Engineer in 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 (RL) to lead advanced research and development of cutting-edge AI models. These systems will integrate foundational Bayesian frameworks with Mixture of Models, multi-pass sharded systems, multitask and multi-objective optimization, external knowledge incorporation, and Large Language Models (LLMs) and Large Multimodal Models (LMMs) with reasoning, planning, and decision-making capabilities.

The role focuses on creating a foundational model fabric that integrates diverse model ecosystems, performs efficiently at scale, and operates in live systems that directly affect product and user experience. The position will help develop next-generation AI platforms for personalization, decision-making, and intelligence across Airbnb applications.

Responsibilities

Research and Innovation

• Lead applied research in Bayesian systems, Distributional Reinforcement Learning, and multimodal architectures for ranking, recommendations, personalization, and long-tail discovery.
• Bridge theoretical AI/ML advances with real-world production systems.
• Ensure research can be applied and scaled to practical business needs.

Architecture and Design

• Define and drive the architecture of large-scale Bayesian framework-based AI systems.
• Develop multi-pass sharded Bayesian, discriminative, and generative single-agent and multi-agent systems.
• Incorporate Mixture of Models and Agents, multitask learning, multi-objective optimization, and external knowledge systems.
• Develop methods to interoperate with LLMs, LRMs, LMMs, and transformer-based architectures using AI multi-agent frameworks.

Model Development

• Build and refine Bayesian or Markovian graph chains for uncertainty estimation, adaptive decision-making, and probabilistic reasoning.
• Develop foundational models combining Bayesian techniques, classical machine learning, LLMs, LMRs, LMMs, and other advanced architectures.
• Improve scalability, performance, and robustness so systems can absorb and adapt to diverse data sources and paradigms.

Technical Leadership and Collaboration

• Lead technical direction and strategy for AI/ML systems.
• Influence engineering leaders, product managers, and data scientists to adopt unified intelligence platform approaches.
• Perform code reviews, mentor engineers, and champion AI/ML best practices.
• Work with structured and unstructured data to design models for diverse use cases.
• Collaborate with cross-functional partners to identify opportunities, refine requirements, and deliver impactful solutions.
• Translate complex technical decisions into business value.

Operational Excellence

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

Requirements

• 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 writing code and deploying production systems.
• Strong programming skills in Python, Scala, Java, or C++.
• Expertise with AI/ML frameworks such as TensorFlow and PyTorch.
• Proven experience with Bayesian neural networks, Bayesian learning, and reinforcement learning.
• Strong background in probability, statistics, and optimization.
• Experience building scalable AI/ML systems with technologies such as Spark, Kafka, and distributed architectures.
• Familiarity with Mixture of Models, ensemble techniques, multitask learning, and sharded architectures.

Preferred Qualifications

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

Location

This position is US remote eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with the manager. The employee must live in a state where Airbnb, Inc. has a registered entity; some states are excluded. If employed by another Airbnb entity, the recruiter will provide the eligible states.

Benefits

The role may be eligible for a bonus, equity, benefits, and Employee Travel Credits. Airbnb supports an inclusive application and interview process and provides reasonable disability accommodations.

Compensation

The base pay range is $296,000–$370,000 USD per year. Actual base pay depends on factors including training, transferable skills, work experience, business needs, and market demands.