Principal Machine Learning Scientist

Expedia Group brands power global travel for everyone, everywhere. We design cutting‑edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and we know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

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.

• 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.

• Ph.D. or M.S. 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 Tensor Flow, 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‑art in search and recommendations.

• 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.

The total cash range for this position in San Jose is $ to $. Employees in this role have the potential to increase their pay up to $, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the…