Expedia Group Logo

Expedia Group

Machine Learning Scientist III - Personalization

Posted 3 Hours Ago
Be an Early Applicant
Hybrid
San Jose, CA
149K-239K Annually
Senior level
Hybrid
San Jose, CA
149K-239K Annually
Senior level
Develop and productionize machine learning systems for personalization, ranking, recommendations, retrieval, and adaptive customer experiences. Design experiments, evaluate model performance, engineer features, prepare data, and improve model quality. Collaborate with engineering, product, analytics, and science teams on scalable ML services, APIs, data models, deployment, monitoring, and operational performance. Apply deep learning, recommender systems, sequential modeling, embeddings, experimentation, and MLOps practices in large-scale consumer environments.
The summary above was generated by AI

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, 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, 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.

Similar Jobs at Expedia Group

3 Hours Ago
Hybrid
173K-299K Annually
Senior level
173K-299K Annually
Senior level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Develop and productionize machine learning systems for personalization, recommendation, ranking, retrieval, traveler understanding, and sequential modeling. Lead end-to-end scientific work including problem formulation, data exploration, feature engineering, model development, experimentation, evaluation, and operationalization. Collaborate with engineering, product, and business stakeholders on system and API design, mentor other scientists, influence technical direction, and apply advanced deep learning and foundation-model techniques at scale.
Top Skills: APIsData ModelingDeep LearningEmbedding ModelsFoundation ModelsGenerative RetrievalInformation RetrievalLarge Language Models (Llms)Machine LearningRanking SystemsRecommendation SystemsSemantic RetrievalSequential ModelingTransformer Models
3 Hours Ago
Hybrid
185K-319K Annually
Senior level
185K-319K Annually
Senior level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Lead product security architecture across Expedia Group: advise engineering and product teams, run threat modeling and architecture reviews, embed security and privacy into roadmaps, drive AI-enabled security automation and continuous verification, mentor teams, and shape long-term security strategy for cloud-native, microservices environments.
Top Skills: Agentic ArchitecturesAi/MlAWSCi/CdContainerizationContext EngineeringDockerGenerative AiKubernetesMcpsMicroservicesSdksSecret And Certificate ManagementToken-Based Authentication
3 Hours Ago
Hybrid
200K-320K Annually
Senior level
200K-320K Annually
Senior level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Lead new business development and strategic partner growth for Expedia Group Advertising. Own the full sales cycle from prospecting and solution development through negotiation, closing, and renewals. Manage enterprise partner relationships, build pipelines, develop tailored advertising solutions, collaborate cross-functionally, use market and revenue insights for territory planning, maintain CRM accuracy, achieve revenue targets, and coach peers.
Top Skills: CRMSalesforceSlack

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account