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.
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, traveler representations, and other adaptive experiences throughout the traveler journey.
We are looking for a Machine Learning Scientist II to help develop the deep learning foundations behind these experiences. The role spans neural recommendation and ranking, representation and sequential learning, and emerging applications such as agent personalization, memory, and evaluation.
This is a hands-on applied science role for someone with strong machine learning fundamentals who wants to deepen their expertise in modern deep learning while working with experienced scientists and engineers on large-scale, real-world systems.
Develop, evaluate, and refine machine learning models to solve clearly defined business problems, including tasks such as prediction, ranking, recommendation, and optimization for Expedia Group products and services.
Design and implement end-to-end ML workflows, including data exploration, feature engineering, model training, validation, and A/B experimentation, ensuring robust measurement of impact and model performance.
Collaborate with software engineers, data scientists, product managers, and other stakeholders to integrate ML solutions into production systems, focusing on reliability, scalability, and maintainability.
Analyze large-scale, real-world datasets to uncover insights, identify opportunities for model and feature improvements, and communicate findings and tradeoffs to both technical and non-technical audiences.
Apply sound statistical and machine learning principles, including model evaluation, error analysis, and bias/variance tradeoffs, to improve model quality and ensure responsible use of data and algorithms.
Demonstrate familiarity 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.
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field, or equivalent practical experience.
Professional experience applying machine learning or statistical modeling to real-world problems, including building, evaluating, and deploying models to production environments.
Hands-on experience with core ML and data technologies appropriate for this level—for example, Python, deep learning frameworks such as PyTorch, TensorFlow, Keras, or JAX, and data processing tools—and with designing, implementing, and evaluating deep learning models and end-to-end ML pipelines or services.
Ability to independently own well-scoped ML problem areas or components within a larger system, collaborating with cross-functional partners to deliver measurable business impact.
Familiarity 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.
Advanced degree (Master’s or PhD) in Machine Learning, Computer Science, Statistics, or a related quantitative discipline with a focus on applied machine learning, deep learning, or statistical modeling.
Demonstrated experience taking deep learning models from concept through experimentation and iteration, with exposure to deployment, monitoring, or scaled adoption in production systems.
Experience with neural recommendation, ranking, retrieval, two-tower models, or learned embeddings and representations for travelers, items, sequences, or other structured entities.
Experience developing sequential models, transformers, or attention-based architectures, including model design and evaluation beyond applying a standard pretrained-model fine-tuning recipe.
Evidence of scientific curiosity through implementing recent research, academic publications, substantial research projects, open-source contributions, internships, or relevant competitions.
Exposure to large-scale data processing, ETLs, training pipelines, A/B experimentation, model serving, monitoring, or other production ML practices.
Interest or experience in agent personalization, learned memory, LLM evaluation, or hybrid LLM-recommender systems grounded in rigorous modeling and experimentation rather than only out-of-the-box APIs or retrieval-augmented generation workflows.
Accommodation requests
Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.
About Expedia Group
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.
Important notice
Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.
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.Skills Required
- Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related field, or equivalent practical experience.
- Professional experience applying machine learning or statistical modeling to real-world problems, including building, evaluating, and deploying models to production.
- Hands-on experience with core ML and data technologies such as Python and deep learning frameworks (PyTorch, TensorFlow, Keras, or JAX).
- Experience designing, implementing, and evaluating deep learning models and end-to-end ML pipelines or services.
- Ability to independently own well-scoped ML problem areas and collaborate cross-functionally to deliver measurable business impact.
- Familiarity with AI-driven systems, tools, or workflows and safely integrating AI/ML-enabled solutions in products.
- Advanced degree (Master's or PhD) in a quantitative discipline with focus on applied ML, deep learning, or statistical modeling.
- Experience with neural recommendation, ranking, retrieval, two-tower models, learned embeddings, or related architectures.
- Experience developing sequential models, transformers, or attention-based architectures and performing model design beyond off-the-shelf fine-tuning.
- Exposure to deployment, monitoring, large-scale data processing, ETLs, training pipelines, A/B experimentation, and production ML practices.
- Interest or experience in agent personalization, learned memory, LLM evaluation, or hybrid LLM-recommender systems.
- Evidence of scientific curiosity through research, publications, open-source contributions, substantial projects, internships, or competitions.
Expedia Group Compensation & Benefits Highlights
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Wellbeing & Lifestyle Benefits — Travel and wellness reimbursements, employee travel discounts, and flexible stipends are presented as standout perks that add meaningful lifestyle value. Mental-health resources and pet support broaden the package beyond core pay.
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Parental & Family Support — Paid parental leave for all parents with additional time for birthing parents, plus adoption, surrogacy, and caregiver support, are highlighted as generous and accessible. Immediate eligibility for parental leave reinforces the family-friendly design.
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Healthcare Strength — Medical, dental, and vision coverage is paired with inclusive healthcare extending to partners and covering fertility and transgender services. Access to mental-health platforms complements the core medical offering.
Expedia Group Insights
What We Do
Expedia Group, Inc. is the global travel marketplace with one purpose: to help travelers explore the world, one journey at a time. Expedia Group™ connects travelers, partners, and advertisers through its trusted brands, leading technology, and rich first-party data, delivering predictive, personalized experiences that shape the future of travel. Expedia Group’s ecosystem includes three flagship consumer brands – Expedia®, Hotels.com®, and Vrbo® – the largest B2B travel business, and a premier advertising network. Guided by an experienced and passionate global team, Expedia Group helps millions of travelers in more than 70 countries explore the world with confidence and ease.
Why Work With Us
Life at Expedia Group starts with the people and is shaped by how we work together. You’ll join a global community of curious teammates from different backgrounds, locations, and disciplines. Day to day, that means sharing ideas, taking ownership, and solving problems together.
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Expedia Group Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.


