Expedia Group

Machine Learning Scientist III - Personalization

Expedia Group
US San Jose, CA, US
Onsite 2026-06-24
Announced salary
$149k–$238k
Low
$116K
Median
$153K
High
$202K
Market in San Jose · BLS OEWS 2025

Job description

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 flexible work model (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 the team** The Unified Personalization Service team is part of Expedia Product \& Technology. UPS is building Expedia Group's centralized, real\-time personalization engine across brands and channels, powering ranking, recommendations, retrieval, and other adaptive experiences that help travelers see more relevant, contextual, and useful experiences throughout their journey. We are looking for a Machine Learning Scientist III to help build production ML systems for personalization, with emphasis on deep learning, neural recommender systems, sequential and session\-based modeling, embeddings, scalable experimentation, and reliable model deployment. This is a hands\-on applied science and engineering role for someone who can contribute across model development, experimentation, data pipelines, deployment, and production model quality. **In this role, you will** * Develop, apply, and advance machine learning solutions for personalization use cases, translating business and customer problems into scalable scientific approaches and production\-ready models. * Design experiments, evaluate model performance, an

On the map

map

See this employer on the map — San Jose

← See all AI / ML Engineer · San Jose