Principal Machine Learning Scientist - Search and Recommendations

Expedia•San Jose, WA

About The Position

Expedia Group is seeking a Principal Machine Learning Scientist to join the Travel Search & Discovery team. This role will lead the development and optimization of AI models for Expedia’s Search & Recommendation systems, including natural language search, multi-modal search, Recommendations, and generative AI-based discovery. The ideal candidate is a deep learning expert capable of creating effective AI solutions for search and recommendations, focusing on innovation and implementing cutting-edge technology. This is a significant opportunity to build foundational systems within Expedia’s AI-first strategy.

Requirements

PhD, or MS, in Computer Science, Machine Learning, Statistics, Engineering, or a related field; or equivalent professional experience
10+ 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
Demonstrated ability to mentor and technically lead research or engineering teams
A passion for building user-centric AI products and a keen curiosity about advancing the state-of-the-art in search and recommendations

Nice To Haves

Experience in the travel or e-commerce industry
Familiarity with cloud platforms (AWS, GCP, Azure)
Publications in top-tier ML conferences or journals
Contributions to open-source ML projects
Experience in personalization systems
Experience taking models from prototype to production in collaboration with Machine Learning Engineering teams

Responsibilities

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