Senior Machine Learning Scientist, Recommendation Systems

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 global hybrid work setup (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.

Senior Machine Learning Scientist, Recommendation Systems

Introduction to the team

The Recommendation Data Science team is dedicated to developing large-scale, industry-leading recommender systems that help millions of travelers to discover captivating destinations, perfect accommodations, and unforgettable experiences worldwide. Collaborating closely with product and engineering teams across Austin, Seattle, and London, our systems power over 70 placements across Expedia, Hotels.com, and Vrbo brands. Join us in shaping the future of travel and making a difference for millions of explorers around the globe!

Our team is seeking a Senior Machine Learning Scientist who is passionate about building systems that create measurable business value. In this role, you will design, develop, and work with engineers to deploy cutting-edge recommendation systems that personalize user experiences, enhance engagement, and drive measurable business impact. This is an opportunity to work on large-scale, complex datasets and build solutions that directly affect millions of travelers worldwide.

In this role, you will:  

• Hands-on develop machine learning models and pipelines at scale, including both batch and real-time use cases

• Work collaboratively with cross-functional partners including software engineers, product managers, data engineers and data analyst, identify opportunities for business impact, understand, refine and prioritize

• Stay updated on the latest advancements in ML, recommender systems, and AI technologies, and apply them to develop innovative solutions. A track record in raising and maintaining a high technical bar in data science organization

• Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning

Experience and qualifications:

• Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field with 5+ years of hands-on experience in developing recommender systems or retrieval/ranking systems at scale

• Proven experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras) and proficiency in programming languages like Python or Scala

• Proven technical experience in at least one of the following fields: ranking algorithms, candidate retrieval, deep learning neural network (e.g. embeddings, transformers), reinforcement learning, graph-based algorithms and GenAI

• Versatility to communicate clearly with both technical and non-technical audiences. (e.g. product, stakeholders, engineers and analytical teams)

Preferred Qualifications

• Experience working with real-time recommender systems and personalization engines

• Familiarity with cloud platforms (AWS) and MLOps tools

• Contributions to the research community through publications, presentation or open-source projects

The total cash range for this position in Austin is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, 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.

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 Forbes, TIME, Disability: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. CST: 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, or veteran status. 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.