[Hiring] Principal AI/ML Researcher / Engineer In Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning @Airbnb

Role Description

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
• 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.

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.

Requirements

• Lead groundbreaking applied research in Bayesian systems, distributional reinforcement learning, and multi-modal architectures.
• Bridge the gap between theoretical AI/ML advancements and real-world production systems.
• 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.
• 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.
• Continuously improve systems for scalability, performance, and robustness.
• Lead technical direction and strategy for AI/ML systems.
• Influence cross-functional teams to adopt unified intelligence platform approaches.
• Perform code reviews, mentor engineers, and champion best practices in AI/ML.
• 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.
• 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.

Benefits

• Base pay range: $296,000 — $370,000 USD.
• Role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Company Description

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.