Machine Learning Scientist III - Personalization

Posted Yesterday
Be an Early Applicant
San Jose, CA, USA
Hybrid
149K-239K Annually
Senior level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Helping travelers explore the world. One journey at a time.
The Role
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.
Summary Generated by Built In

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.

Skills Required

  • 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 machine learning solutions
  • Ownership of machine learning solutions within a service, multi-service, or domain-level scope, including accountability for model quality, experimentation, and operational performance
  • Strong foundation in machine learning methods, statistical analysis, experimentation, feature engineering, and working with large-scale production datasets
  • 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
  • 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
  • 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

What the Team is Saying

Christos Rigas

Expedia Group Compensation & Benefits Highlights

  • Wellbeing & Lifestyle Benefits Travel and wellness stipends, employee travel discounts, and access to industry credentials create distinctive lifestyle value aligned with the company’s mission. Feedback suggests these perks are widely valued and complemented by programs like charitable matching and volunteer time.
  • Parental & Family Support Paid parental leave for all parents, additional time for birthing parents, caregiving leave, and fertility/family‑building support indicate comprehensive family backing. Immediate eligibility and flexible return‑to‑work options further strengthen this area.
  • Healthcare Strength Employer‑provided medical options are positioned as locally competitive and are supplemented by mental‑health platforms and neurodiversity coaching. Health coverage is regarded positively, with multiple support pathways beyond standard insurance.

Expedia Group Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Seattle, WA
16,000 Employees
Year Founded: 1996

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.

Gallery

Gallery
Gallery
Gallery
Gallery
Gallery

Expedia Group Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
HQSeattle, WA
JP
VE
HK
MY
Amsterdam, NL
Antalya, TR
Athens, GR
Auckland, NZ
Austin, Texas
Bangkok, TH
Barcelona, ES
Beijing, CN
Bengaluru, Karnataka
Berlin, DE
Bothell, US
Brisbane, AU
Brussels, BE
Chicago, US
Cologne, DE
Copenhagen, DK
Dallas, US
Denpasar, ID
Dubai, AE
Dublin, IE
Edinburgh, GB
Fort Lauderdale, US
Geneva, CH
Gurugram, Haryana
Gurugram, IN
Hanyang, KR
Ho Chi Minh, VN
Issaquah, US
İstanbul, TR
Johannesburg, ZA
Kailua-Kona, US
Kilkattalai, JO
Lahaina, US
Lisbon, PT
London, GB
Lyon, FR
Madrid, ES
Manila, PH
Marseille, FR
Melbourne, AU
Miami, US
Milan, IT
Mohokare, ZA
Montréal, CA
Munich, GD
Paris, FR
Poipu, US
Praha, CZ
Rome, IT
San Francisco, California
San Leonardo, PH
Sham Chun Hu, CN
Shanghai, CN
Singapore, SG
Springfield, US
Stockholm, SE
Sydney, AU
Taipei City, TW
Tokyo, JP
Toronto, CA
Wrocław, PL
Learn more

Similar Jobs

Expedia Group Logo Expedia Group

Scientist

AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Hybrid
San Jose, CA, USA
16000 Employees
173K-299K Annually

Expedia Group Logo Expedia Group

Architect

AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Hybrid
San Jose, CA, USA
16000 Employees
185K-319K Annually

Expedia Group Logo Expedia Group

Business Development Manager

AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Hybrid
San Diego, CA, USA
16000 Employees
200K-320K Annually

Expedia Group Logo Expedia Group

Business Development Manager

AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Hybrid
West Hollywood, CA, USA
16000 Employees
200K-320K Annually

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account