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.

About the team

We are the Model Lifecycle team inside Expedia Group's ML Platform. Our services help the MLS and MLE community across EG take use cases from idea to production model in the shortest time possible, with paved paths for training, registration, deployment, serving and monitoring.

As an SDE III you will own features end to end across one or two of these services, working in Python, Go, TypeScript and Kubernetes, with senior and principal engineers close by to pair, review and unblock. Hundreds of models across Expedia, Vrbo and Hotels.com run on what we help build, so the code you ship is felt quickly and good engineering habits (tests, observability, clear PRs) are valued as much as raw output.

We lean heavily on coding agents (Cursor, Claude Code and friends) to accelerate the delivery cycle: scaffolding services, drafting tests, reviewing PRs and keeping documentation in step with the code. You'll have space to learn how to get the best out of them and we'll look to you to apply good judgment on what lands in main.

In this role, you will:

• Design, develop, test, deploy, and maintain reliable software services and applications that deliver measurable outcomes for customers and the business.
• Apply software engineering principles across the development lifecycle, including low-level system design, API design, data modelling, implementation, testing, and code review.
• Own technical solutions within a service or defined technical area, making sound engineering decisions that balance maintainability, scalability, reliability, and delivery.
• Collaborate across engineering and partner teams to define requirements, resolve dependencies, and deliver cohesive solutions across multiple domains when needed.
• Use operational data, monitoring, and production feedback to troubleshoot issues, improve system performance, and strengthen the reliability of owned services.
• Safely integrate and operate AI/ML-enabled solutions that improve outcomes, applying familiarity with AI-driven systems, tools, or workflows and AI/ML concepts to real-world products.