Principal Machine Learning Scientist - Search and Recommendations

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Introduction to the Team Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.   We are looking for a Principal Machine Learning Scientist to join our growing Travel Search & Discovery team. This Principal will lead the development and optimization of Expedia’s Search & Recommendation AI models including natural language search, multi-modal search, Recommendations, and generative AI–based discovery. The ideal candidate for this position is a true deep learning expert who can develop effective AI solutions for search and recommendations. Innovation and developing cutting-edge technology as well as implementing industry-leading solutions are key responsibilities of this role. This is a rare opportunity to build foundational systems in a high-impact domain, backed by Expedia’s AI-first vision. In this role, you will:  Drive the research, design, and deployment of advanced machine learning solutions for large-scale search and recommendation systems Architect hybrid multi-modal retrieval frameworks, combining text, image, and structured data to power relevant and diverse content discovery Develop and optimize multi-stage ranking pipelines, leveraging deep learning, generative retrieval, and other advanced algorithms to maximize relevance and engagement Lead efforts on intent understanding, utilizing user queries, behavioral signals, and context for superior search and recommendation accuracy Advance personalization strategies using embeddings, user-item modeling, and context-aware algorithms to tailor content to individual users Pioneer cutting-edge sequential recommender systems that account for evolving user preferences, session context, and temporal dynamics Design robust offline and online evaluation methodologies, including A/B testing, counterfactual estimation, and metric development Collaborate closely with cross-functional engineering and product teams to translate business needs into machine learning problems and production-ready solutions Mentor and guide a team of scientists, driving best-in-class research and deployment practices Minimum Qualifications: PhD, or MS, in Computer Science, Machine Learning, Statistics, Engineering, or a related field; or equivalent professional experience 1 0+ years of related industry experience Experience building production-grade search, recommendation or personalization systems Strong understanding of intent understanding techniques, retrieval methods, deep learning for recommendations, reinforcement learning, and causal inference Proficiency in Python and ML frameworks such as TensorFlow, JAX, or PyTorch Experience with large-scale distributed systems and big data technologies (e.g., Spark, Hadoop) Familiarity with A/B testing and experimentation methodologies Ability to work with large-scale, real-world data with attention to bias, fairness, and privacy · Excellent communication skills for both technical and non-technical audiences