Senior Machine Learning Engineer, Supply & Competitive Intelligence

The Community You Will Join:

Marketplaces Data and AI is a group of passionate machine learning, software, data, and analytics engineers. We are responsible for developing new, cutting-edge AI and data products that leverage Airbnb’s massive datasets across Users, Listings, Pricing, and Supply/Demand. You will be a crucial part of the Guest and Host organization, building the intelligence that powers the web and native apps used by hundreds of millions of guests and hosts globally.

The Difference You Will Make:

Supply & Competitive Intelligence sits at the intersection of Data/AI and Airbnb's competitive strategy. As the engineer leading crawling infrastructure for the Competitive Intelligence platform, you will build the systems that give Airbnb a real-time, comprehensive view of the global travel market — how competitors price, list, and supply their inventory across every market Airbnb operates in.

Your work will directly shape Airbnb's understanding of its competitive landscape, feeding ML models and data products that inform pricing strategy, supply growth, and product decisions for hundreds of millions of guests and hosts around the world.

A Typical Day:

• Design and deploy ML models that extract and structure competitive intelligence signals — supply availability, pricing patterns, and market saturation — from large-scale crawled datasets across global competitors
• Build and maintain end-to-end ML pipelines spanning feature engineering, offline training, and low-latency online serving, ensuring high data fidelity and resilience to upstream schema drift
• Apply entity resolution and matching techniques to accurately map competitor listings and markets to Airbnb's internal supply taxonomy, using methods such as embedding models, gradient boosted trees, and transformer-based architectures
• Partner with the crawling infrastructure engineer, data engineers, and product teams to translate competitive intelligence needs into well-defined ML problem formulations and measurable success criteria
• Run rigorous offline and online experiments to evaluate model quality, and collaborate with Pricing, Supply Growth, and Strategy stakeholders to turn model outputs into actionable business decisions
• Stay current with the latest advances in ML and AI, identifying opportunities to incorporate new techniques into the competitive intelligence platform

Your Expertise:

• 5–10 years of professional experience in applied Machine Learning, with a proven track record of architecting and deploying high-impact models into production at global scale.
• Exceptional programming proficiency in Python (required), with additional experience in Scala, Java, or similar languages for building robust backend systems.
• Deep mastery of ML fundamentals and best practices—including feature engineering, model selection, A/B testing, and training/serving skew mitigation—alongside advanced algorithms like gradient boosted trees, neural networks, and transformers.