Senior Manager, Machine Learning Science - Bundled Products Recommendations

Expedia Expedia · Hospitality · Seattle, WA

Senior Manager, Machine Learning Science for Bundled Products Recommendations at Expedia. The role involves leading a team to develop and deploy ranking and recommendation models for travel products, optimizing traveler experiences and business goals. It requires defining roadmaps, setting best practices for experimentation and evaluation, and partnering with engineering teams for productionization. Experience with GenAI and agentic techniques is preferred.

What you'd actually do

  1. Enable a team to develop industry-leading ranking & recommendation models for the travel industry to enable travelers to have memorable travel experiences
  2. 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
  3. 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
  4. 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
  5. 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

Skills

Required

  • 8+ years of relevant professional experience
  • 3+ years of people management experience
  • Strong expertise in modern machine learning methods in ranking and recommendation
  • solid programming skills
  • 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

Nice to have

  • 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 multi-service or multi-domain ML systems
  • Experience designing and operationalizing experimentation platforms, advanced measurement frameworks, or causal inference methodologies to drive data-informed decision making at scale
  • Leadership experience in raising the technical bar for ML teams through publication-quality analyses, reusable modeling frameworks, rigorous data and model quality practices, and effective documentation
  • Proven ability to advance a team’s capabilities with emerging AI/ML techniques and tooling, including GenAI & agentic techniques, to unlock new product experiences and operational efficiencies

What the JD emphasized

  • Senior Manager, Machine Learning Science
  • Bundled products ranking, recommendations, and intent modeling
  • own our Bundled products ranking, recommendations, and intent modeling
  • multiple high traffic, live models
  • 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
  • Proven experience managing or technically leading machine learning scientists or applied researchers, with ownership spanning multiple services, products, or problem spaces
  • Demonstrated track record delivering large-scale machine learning solutions in high-traffic, data-rich environments, including setting technical direction and architecture for multi-service or multi-domain ML systems

Other signals

  • owns multiple high traffic, live models
  • significant scope for further growth
  • apply familiarity with AI-driven systems, tools, or workflows and AI/ML concepts to real world products