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.
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.
Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
Introduction to Team
Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
This Machine Learning Engineer role is part of the Distribution & Supply team which sits within our Technology division. The Distribution & Supply team builds and optimizes the machine learning–driven systems that power how our travel supply is connected, priced, and surfaced across Expedia Group’s global marketplace, ensuring partners can efficiently reach travelers with the right inventory at the right time. In this role, you will apply advanced machine learning engineering to design, deploy, and scale robust models that directly improve the quality and performance of our distribution platform for both travelers and partners.
In this role, you will:
Design and implement scalable machine learning solutions across multiple domains, ensuring technical rigor and robust architecture.
Develop and deploy machine learning models, including data preprocessing, feature engineering, and model evaluation.
Collaborate cross-functionally to integrate ML systems with existing products and services, promoting technical excellence and innovation.
Drive system design, including low-level design (LLD), API design, and data modeling to support real-time and batch ML workflows.
Safely integrate and operate AI/ML-enabled solutions that improve outcomes, leveraging modern AI/ML concepts and best practices.
Contribute to technical discussions, code reviews, and knowledge sharing to foster a culture of continuous improvement and high-quality software delivery.
Experience and Qualifications:
Minimum Qualifications:
Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
3+ years of relevant professional experience.
Demonstrated ownership of end-to-end machine learning projects, from data exploration through model deployment in production.
Proficiency in programming languages such as Python or Java, and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products
Preferred Qualifications:
Experience operating machine learning solutions at scale, with an emphasis on reliability, performance, and maintainability.
Experience in designing and implementing ML systems within multi-service environments.
Proven ability to implement automated monitoring, testing, and retraining pipelines for ML models.
Demonstrated expertise in integrating AI/ML capabilities into large-scale applications, ensuring responsible use of data and model outcomes.
Knowledge of responsible AI practices, including model fairness, interpretability, and compliance within product environments.
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, religion, gender, sexual orientation, national origin, disability or age.Expedia Group Melbourne, Victoria, AUS Office
447 Collins Street, Melbourne, Australia, 3000
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