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Expedia Group is offering a hands-on ML internship where you will design and prototype ML models, work on real business priorities, and learn through structured onboarding and mentorship. You will collaborate across teams to deliver measurable ML solutions and gain exposure to production-ready workflows.
This program emphasizes practical skill-building and professional development. Interns will engage in projects that influence travel search and recommendations, while expanding their network
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.
*Note: Applications will remain live for at least 5 business days when the role is posted. The post will be removed when application targets are met.
Travel is so much more than simply reaching your destination. Along the way you will make an immediate impact on reimagining the way people search for travel with our awesome team by inventing brand-new techniques to power global travel for everyone, everywhere. From building pipelines and prototyping new ML models with A/B testing, to applying new techniques to services that run tens of thousands of requests per second, there is no shortage of opportunities for technical innovation at Expedia Group - the sky's the limit!
Design, prototype, and evaluate machine learning models under the guidance of more experienced machine learning scientists, contributing to well-scoped research and product-focused experiments.
Implement clean, maintainable model training and inference code using standard Software Engineering practices, including basic unit testing, code reviews, and reproducible experimentation workflows.
Participate in low-level system design, API design, and data modeling for ML-powered features, learning how to translate product and data requirements into robust, production-aware ML solutions.
Explore, analyze, and prepare data using fundamental statistical and ML techniques to improve model quality, robustness, and fairness, including feature engineering and basic error analysis.
Collaborate with peers, mentors, data scientists, engineers, and product partners to understand problem spaces, define success metrics, and iterate on ML solutions that deliver measurable impact.
Learn to work with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including safely integrating and operating AI/ML-enabled solutions that improve outcomes within defined guidance and scope.