Principal AI Scientist: Large-Scale Search & Personalization

Expedia, Inc.; Seattle (WA); On-site; USD 224,000 - 314,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision coverage

Paid time off

Employee Assistance Program

Wellness programs

Travel reimbursement

Travel discounts

IATAN membership

Job summary

Expedia Group is seeking a Principal Applied Scientist to join the Personalization, Search & Recs team in Seattle/San Jose. You will drive research, design, and deployment of advanced ML models for search and recommendations, including multi-modal retrieval and personalized content.

You will lead a team of scientists, collaborate with product & engineering, and shape our AI-first travel platform. The role emphasizes production-grade systems, scalable pipelines, and responsible AI with bias and

Qualifications

• 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

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

Skills

Machine learning

Deep learning

Search systems

Recommender systems

Distributed computing

A/B testing

Bias and fairness

Communication

Mentoring

Cloud platforms

Education

PhD or MS in Computer Science / ML / Statistics or related

Tools

Python

TensorFlow

PyTorch

JAX

Spark

Hadoop

AWS/Azure/GCP

Job description

Expedia Group is seeking a Principal Applied Scientist to join the Personalization, Search & Recs team in Seattle/San Jose. You will drive research, design, and deployment of advanced ML models for search and recommendations, including multi-modal retrieval and personalized content.

You will lead a team of scientists, collaborate with product & engineering, and shape our AI-first travel platform. The role emphasizes production-grade systems, scalable pipelines, and responsible AI with bias and