Machine Learning Engineer III, ML Operations
Company: Expediagroup
Location: India - Bangalore
Type: Full-time
Posted: 2026-08-24
About this role
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
We create and deliver an aligned, dedicated marketing strategy to fuel each Expedia Group brand's success. Since our travelers interact with us through our brands, we maintain a brand-focused approach in our marketing while leveraging the scale and efficiency we’ve built through functional expertise.
The Meta/SEM Bidding Programs team at Expedia Group is looking for a Machine Learning Engineer III who mentors junior engineers, applies modern data and ML engineering principles to improve existing systems, and leads complex, well-defined projects in a high-scale production environment.
In this role, you will:
- Collaborate with peers and stakeholders across the organization to understand cross-dependencies, shape solutions, and translate experimental DS workflows into robust production pipelines.
- Develop, refactor, and test complex ML and software components, applying solid software engineering practices (design principles, data structures, design patterns) to produce clean, maintainable, and optimized code.
- Contribute to the design of **big data and ML applications**, including how models are trained, evaluated, and served at scale across batch and streaming (online) inference workflows...