Machine Learning Scientist II

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:

• Tackle business problems by applying reinforcement learning models, algorithms, and techniques using in-house and open-source libraries.
• Apply an understanding of supervised learning, unsupervised learning, and reinforcement learning theory, modifying and adapting models to suit business needs.
• 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).
• 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 master’s degree or Ph.D. in Computer Science, Statistics, Math, Engineering, or a related technical field; or equivalent related professional experience.
• You have significant experience with Python, Scale and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and data processing frameworks (e.g., Spark).

• You have demonstrated ability to build and maintain machine learning applications in production environments.
• You have a solid understanding of hypothesis testing.
• Preferred: You are familiar with multi-armed bandit algorithms (e.g., Thompson Sampling, Upper Confidence Bound), reinforcement learning frameworks, and sequential decision-making techniques.
• Preferred: You have experience with real-time recommendation systems, user behavior modeling, and optimizing machine learning models for cold-start scenarios or environments with sparse data.

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 portal.

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.

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.