Machine Learning Scientist III - Personalization

About this role

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, 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, and use data-driven methods to improve relevance, ranking, recommendation, and overall customer experience across personalization systems.

• Partner across engineering, product, analytics, and science teams to define solution approaches, influence technical direction, and deliver ML capabilities that can operate across multiple products and domains.

• Contribute technical depth in model development, feature design, data preparation, offline and online evaluation, and the operationalization of machine learning solutions in production environments.

• Apply strong technical judgment to system design, API design, data modeling, and low-level solution design that support robust, maintainable, and extensible ML-powered services.

• Safely integrate and operate AI/ML-enabled solutions that improve outcomes, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.

Minimum Qualifications • Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, a related technical field, or equivalent professional experience.

• 5+ years of relevant experience in machine learning, applied science, data science, or software development, including delivering production-grade ML solutions.

• Demonstrated ownership of machine learning solutions within a service, multi-service, or domain-level scope, with accountability for model quality, experimentation, and operational performance.

• Strong foundation in machine learning methods, statistical analysis, experimentation, feature engineering, and working with large-scale datasets in production environments.

• Proficiency in software engineering practices for scientific systems, including coding, low-level design, API design, data modeling, and collaboration with engineering teams to productionize solutions.

Preferred Qualifications • Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related technical field.

• Experience building and scaling personalization, recommendation, ranking, retrieval, or relevance models in large, complex consumer-facing environments.

• Experience with neural recommendation systems, sequential or session-based recommendation, transformer-based recommenders, semantic retrieval, or representation learning at scale.

• Experience with foundation models, LLMs, embedding models, semantic IDs, hybrid LLM-recommender systems, or retrieval-augmented personalization workflows.

• Demonstrated ability to use data, metrics, and experimentation to guide prioritization and decision-making while balancing scientific rigor, product impact, and platform scalability.

• Experience with production ML workflows such as model serving, experimentation frameworks, feature or data pipelines, monitoring, model lifecycle management, or MLOps

The total cash range for this position in San Jose is $149,000.00 to $208,500.00. Employees in this role have the potential to increase their pay up to $238,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
 Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Benefits and perks Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life .

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

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