Senior Machine Learning Scientist- Search, Recommendations AI Engineering

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 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.

The Multi-Product AI team at Expedia Group enables unforgettable travel experiences. The team’s responsibilities cover search ranking & recommendations for Brand Expedia across core lines of business including Flights, Cars, Packages, and Activities. Additionally, we’re responsible for optimizing our interactions with travelers across this domain, including cache optimization, price forecasting, and next-best action modeling. Our approaches include both traditional ML as well as GenAI and Agentic AI solutions.

We work closely with other teams in the Data & AI organization to continually improve our tools, processes, and platforms for building and deploying industry leading AI solutions.

The Senior Machine Learning Scientist will be a technical lead for our team’s Generative & Agentic AI projects. You will utilize RAG pipelines, LLM orchestration, MCP servers and other techniques to solve challenging business problems, implement best practices across the team, and act as a full-stack contributor to design, develop, and deploy AI solutions. You will work with a dynamic group of product managers, engineers, and scientists to achieve Expedia’s business goals.

• Enhance our recommendation systems across both agentic & traditional search placements
• Design and implement agentic AI systems and define best practices for the team
• Design agentic systems with capabilities including long-term memory, tool integration, multi-agent collaboration
• Lead end-to-end agent development life cycles, including prompt engineering, RAG, evaluation, deployment, and monitoring
• Utilize MCP for enterprise data/tool connectivity
• Manage stakeholders with frequent communication and expectation management, meeting deadlines and minimizing surprises.
• Build relationships with other AI leads across the company to share knowledge & find collaboration opportunities
• Stay abreast of developments in machine learning & AI via publications and conferences

• Bachelor's, Master’s, or PhD degree in a quantitative field
• 6+ years of industry experience as an AI Engineer or similar role
• 2+ years experience as a technical lead of Agentic AI projects
• Expertise with Python & AI libraries/frameworks such as Pytorch, Tensor Flow, Lang Chain, Llama Index, Hugging Face
• Proven ability to build, deploy, and maintain AI projects in production environments
• Strong experience with LLM orchestration, prompt engineering, RAG pipelines

• Experience with ranking & recommendation systems
• Publications in top-tier ML conferences or journals
• Experience building or integrating MCP servers for tool exposure
• Familiarity with multi-agent/hierarchical agent systems

The total cash range for this position in Austin is $ to $. Employees in this role have the potential to increase their pay up to $, which is the top of the range, based on…