Principal Machine Learning Scientist - Search and Recommendations

Expedia Expedia · Hospitality · Seattle, WA +1

Expedia is seeking a Principal Machine Learning Scientist to lead the development and optimization of AI models for Search & Recommendation systems, including natural language search, multi-modal search, Recommendations, and generative AI. The role involves architecting retrieval frameworks, optimizing ranking pipelines, advancing personalization, pioneering recommender systems, and designing evaluation methodologies. The scientist will collaborate with engineering and product teams, mentor junior scientists, and drive research and deployment practices.

What you'd actually do

  1. Drive the research, design, and deployment of advanced machine learning solutions for large-scale search and recommendation systems
  2. Architect hybrid multi-modal retrieval frameworks, combining text, image, and structured data to power relevant and diverse content discovery
  3. Develop and optimize multi-stage ranking pipelines, leveraging deep learning, generative retrieval, and other advanced algorithms to maximize relevance and engagement
  4. Lead efforts on intent understanding, utilizing user queries, behavioral signals, and context for superior search and recommendation accuracy
  5. Advance personalization strategies using embeddings, user-item modeling, and context-aware algorithms to tailor content to individual users

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • production-grade search, recommendation or personalization systems
  • deep learning for recommendations
  • large-scale distributed systems
  • A/B testing and experimentation methodologies
  • large-scale, real-world data
  • mentor and technically lead research or engineering teams

Other signals

  • AI-first vision
  • develop effective AI solutions for search and recommendations
  • Innovation and developing cutting-edge technology
  • implementing industry-leading solutions
  • build foundational systems