Machine Learning Scientist III - Personalization

Machine Learning Scientist III - Personalization Expedia - 3.8 San Jose, CA Job Details Full-time $149,000 - $238,500 a year 3 hours ago Benefits Health insurance Dental insurance Paid time off Parental leave Employee assistance program Career development plan Vision insurance Employee discount Qualifications Data model design Software engineering Data modeling projects System design Statistical analysis for research System design for system development Collaboration with product development teams Implementation (software development lifecycle) APIs Machine learning (ML) fundamentals Design (software development lifecycle) Feature engineering Full 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, 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. Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee's passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent ( IATAN ) membership. View our full list of benefits . 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 . 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

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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.

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2029030-50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you're confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs . 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, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.