Senior Manager, Machine Learning Science - Bundled Products Recommendations

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.

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 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.

The Whole Trip AI team at Expedia Group enables unforgettable travel experiences. The team’s responsibilities cover search ranking & recommendations for Brand Expedia across core lines of business including Flights, Cars, Packages, and Activities. Additionally, we’re responsible for optimizing our interactions with travelers across this domain, including cache optimization, pricing forecasting, and next‑best action modeling. Our approaches include both traditional ML as well as GenAI‑based solutions.

We work closely with other teams in the Data & AI organization to continually improve our tools, processes, and platforms for building and deploying industry‑leading AI solutions.

• Enable a team to develop industry‑leading ranking & recommendation models for the travel industry to enable travelers to have memorable travel experiences.
• Lead and grow a team of machine learning scientists to deliver production‑grade ML solutions that solve complex business problems and improve traveler and partner experiences across multiple product domains.
• Define and drive the end‑to‑end machine learning roadmap for your area, from problem formulation and data strategy through model design, evaluation, and productionization in close partnership with engineering and product.
• Set and enforce best practices for experimental design, A/B testing, and causal inference to ensure ML‑driven decisions are statistically robust, interpretable, and aligned to business and customer outcomes.
• Partner with data engineering and software engineering teams to ensure ML models are scalable, resilient, observable, and well‑integrated into services, APIs, and data pipelines in production.
• Mentor, coach, and develop ML scientists through technical guidance, peer review, and career development, fostering a culture of scientific rigor, continuous learning, and high‑impact delivery.
• Apply familiarity with AI‑driven systems, tools, or workflows and AI/ML concepts to real‑world products, safely integrating and operating AI/ML‑enabled solutions that improve outcomes across multiple lines of business.

• Bachelor’s Degree or Equivalent Level;
  Technical Degree Preferred.
• 8+ years of relevant professional experience and 3+ years of people management experience.
• Strong expertise in modern machine learning methods in ranking and recommendation with solid programming skills and collaboration experience with engineering teams on system, API, and data design.
• Substantial professional experience leading end‑to‑end machine learning initiatives, including problem definition, data preparation, feature engineering, model development, offline evaluation, experimentation, and integration into production systems.
• Proven experience managing or technically leading machine learning scientists or applied researchers, with ownership spanning multiple services, products, or problem spaces.

• Experience with natural language search and refinement of recommendations using natural language.
• Experience with multi‑modal recommendations across images, structured metadata, and unstructured text.
• Demonstrated track record delivering large‑scale machine learning solutions in high‑traffic, data‑rich environments, including setting technical direction and architecture for…