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About the Role

The Machine Learning Scientist II role on the Lodging Search Ranking AI team develops and optimizes ranking models using state-of-the-art machine learning/genAI techniques to power lodging search and personalized lodging ranking/recommendations. This applied scientist role involves deploying models to production systems and measuring results via A/B testing, directly impacting business results.

Responsibilities

• Develop, implement, and optimize machine learning models that power data‑driven features and products, from problem framing through production deployment and iteration.
• Design and evaluate experiments, offline evaluations, and A/B tests to measure model impact, using statistical rigor to compare alternatives and drive decisions.
• Collaborate with engineers, product managers, and analysts to translate ambiguous business problems into well‑scoped ML solutions, including data requirements, modeling approach, and success metrics.
• Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models are robust, explainable, and performant at scale.
• Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including monitoring model performance, detecting degradation, and driving continuous improvements in production.
• Demonstrate familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real‑world products, contributing reusable methodologies and best practices that can be leveraged across teams and problem spaces.

Requirements

• Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
• 2+ years of relevant professional experience.
• Proven ability to own ML solutions for a well‑defined service or product area, including data exploration, model development, offline and online evaluation, and partnering with engineering for integration.
• Proficiency in at least one major programming language used for ML (such as Python) and common ML/AI frameworks and tooling for model development, training, and evaluation.
• Solid grounding in core ML concepts (e.g., supervised and unsupervised learning, model generalization, overfitting, evaluation metrics), and experience working with real‑world, noisy datasets.
• Advanced degree (Master’s or PhD) in a quantitative field with a focus on machine learning, statistics, or AI, with experience applying research ideas to practical, large‑scale problems.
• Experience designing and operating ML systems at scale, including feature pipelines, model training workflows, and online inference, with attention to latency, reliability, and cost.
• Demonstrated track record of leading the end‑to‑end lifecycle of ML solutions within a product or domain, from ideation and prototyping through experimentation, launch, and ongoing optimization.
• Strong background in experimentation and data‑driven decision making, including designing robust A/B tests, interpreting results, and translating findings into product and model changes.
• Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with at least one of: recommendation systems, ranking, search, personalization, forecasting, or optimization models.

Skills

• Machine Learning
• GenAI
• Data Modeling
• Feature Engineering
• Model Selection
• Python
• ML/AI Frameworks
• Supervised Learning
• Unsupervised Learning
• Model Generalization
• Overfitting
• Evaluation Metrics
• Experimentation
• A/B Testing
• Recommendation Systems
• Ranking
• Search
• Personalization
• Forecasting
• Optimization Models

Experience Level

• 2+ years of relevant professional experience

Education Level

• Bachelor’s degree in Computer Science or a related technical field
• Advanced degree (Master’s or PhD) in a quantitative field with a focus on machine learning, statistics, or AI

About the Company

• Expedia Group helps 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.
• Our Expedia Product & Technology division builds innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A unified, singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences for the traveler and our partners that drive loyalty and customer satisfaction.
• 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.

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, religion, gender, sexual orientation, national origin, disability or age.