Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

Introduction to Team

The Reinforcement Learning (RL) team at Expedia Group applies cutting-edge RL and multi-armed bandit techniques to optimize user experiences at scale, in real-time. Our contextual multi-armed bandit AI platform serves personalized, multivariate user experiences, considers the unique context of each visitor, and quickly adapts to user behavior. This innovative approach enables faster iteration toward optimal product solutions compared to traditional A/B testing and gracefully handles ever-changing content and continuous "cold start" scenarios. Our work drives optimized experiences across hundreds of millions of customer interactions on the Expedia Group travel platform, generating tens of millions of dollars in profit.

Make an Impact!

The Reinforcement Learning Scientist role is part of the Reinforcement Learning team in the Expedia Product & Technology division at Expedia Group. This role focuses on developing and deploying RL-driven algorithms to elevate the customer experience across the entire platform. As a part of this innovative team, you’ll tackle complex, high-impact business problems by delivering optimized, adaptive user experiences in real time. If you’re passionate about applying advanced machine learning techniques to solve dynamic problems, this is the role for you.

In this role, you will: ​

• Apply supervised, unsupervised, and reinforcement learning theory, models, algorithms, and techniques, using in-house and open-source libraries to tackle business problems.
• Write clean, maintainable, and optimized code that enables efficient collaboration on a common codebase shared among Machine Learning Scientists (MLSs) and Machine Learning Engineers (MLEs).
• Collaborate cross-functionally with business partners to define and test complex objective functions;
• Conduct thorough literature reviews to identify and assess promising algorithms that fit business needs, implementing them from scratch when necessary.
• Select appropriate approaches, balancing level of effort and iterative delivery to solve for the objective, not merely the request.
• Influence decision-making and drive results through clear, concise communication, including writing and data visualizations for various audiences.

Who you are:

• You have a MS/MSc or PhD in computer science, electrical engineering, statistics or similarly quantitative field with 3+ years of experience in a similar role
• You have proven experience creating and growing large-scale production learning systems and solving hard problems in industrial ML: computational advertising, large-scale recommender systems, fraud and anomaly detection in non-stationary environments, click-through optimization in eCommerce, etc
• You have experience in Reinforcement Learning including contextual and context-free bandits and off-policy evaluation;
• You have deep experience with programming languages such as Python, Java, Scala; common data tools: Spark, SQL, Kafka, Flink; and popular ML tools, PyTorch, Scikit Learn, Tensorflow RL; Understanding of modern software design and testing: Devops, CI/CD, Unit testing
• You have experience in advanced experimental design (e.g. adaptive designs and A/B testing hypothesis).
• Bonus: You have publications in relevant venues: KDD, COLT, NeurIPS, ICLR, RecSys, ICML, SIGIR

Accommodation requests

If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.

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.