Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you ll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Introduction to the Team 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. We are looking for a Principal Applied Scientist to join our growing Personalization, Search & Recs team. This Principal will be a key contributor to thought leadership, development and optimization of Expedia’s Search & Personalization AI models including natural language search, multi-modal search, recommendations, and generative AI–based traveler experiences. The ideal candidate for this position is a true deep learning, ML expert who can develop effective AI solutions for search and recommendations. Innovation and developing cutting-edge technology as well as implementing industry-leading solutions are key responsibilities of this role. This is a rare opportunity to build foundational systems in a high-impact strategic area, backed by Expedia’s AI-first vision. In this role, you will:  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 Minimum 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 Preferred Qualifications: 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 Seattle is $224,000.00 to $313,500.00. Employees in this role have the potential to increase their pay up to $358,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in San Jose is $242,000.00 to $338,500.00. Employees in this role have the potential to increase their pay up to $387,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future. Benefits and perks Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at careers.expediagroup.com . Accommodation requests Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at expedia.service-now.com job_accommodation . About Expedia Group Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease. Important notice Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is expediagroup.com. The official place to find and apply for roles is careers.expediagroup.com . Equal Opportunity Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

Requirements

Must-haves

Introduction to the Team
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
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

Nice-to-haves

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
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Application prep

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Keywords to mirror

machine learningaimlpythonawsgcpazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Wellness