Machine Learning Scientist III

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

Expedia Technology teams partner with our Product teams to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and employees. A singular technology platform powered by data, machine learning, and AI provides secure, differentiated, and personalised experiences that build loyalty and traveler satisfaction.

The Content AI team develops machine learning capabilities that improve the quality, relevance, and usefulness of content-focused products and services across Expedia Group. Working within the Product & Technology Machine Learning Science and Engineering organisation, you will translate research and experimentation into reliable, scalable production outcomes. The team works across content understanding, review intelligence, search relevance, ranking, recommendations, content moderation, image-based AI applications, and Generative AI experiences used by millions of travelers worldwide.

In this role, you will:

• Develop, evaluate, and improve machine learning models and algorithms for Content AI applications.

• Design and implement end-to-end machine learning solutions, including data preparation, feature engineering, model training, validation, deployment, monitoring, and continuous optimisation.

• Apply statistical analysis, experimentation, and data-driven decision-making to assess model performance and guide technical direction.

• Collaborate with engineers, product managers, applied scientists, and domain experts to translate ambiguous business problems into scalable ML solutions.

• Contribute to system design, low-level design, API development, and data modelling for production machine learning systems.

• Build and operate production solutions using technologies such as Python, TensorFlow, PyTorch, Redis, Airflow, Docker, Kubernetes, and cloud-native infrastructure.

• Design and deploy scalable batch and real-time ML pipelines supporting customer-facing applications.