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Machine Learning Scientist

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Expedia, Inc.
Full Time position
Listed on 2026-07-10
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 187000 - 261500 USD Yearly USD 187000.00 261500.00 YEAR
Job Description & How to Apply Below

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.

Senior Machine Learning Scientist

The Senior Machine Learning Scientist is responsible for building and evaluating GenAI‑ and LLM‑powered solutions and AI agents that improve post‑booking customer experience, including recommendations, customer service, and trip management. Owns end‑to‑end ML and GenAI projects—from problem framing and data preparation through model/agent design, orchestration, deployment, and continuous evaluation. Applies deep expertise in applied ML, Generative AI, and rigorous experimentation to design robust evaluation frameworks (A/B tests, offline metrics, qualitative assessments) that ensure agents are safe, effective, and aligned with business goals.

Partners closely with product, engineering, and operations while mentoring junior scientists and helping define best practices for AI agent development and evaluation.

Are you passionate about using machine learning to improve customer experience at scale? Would you like to work in the fast‑paced, competitive, customer‑focused, and data‑rich world of online travel?

Our Machine Learning and Data Science team is growing. We are looking for a Senior Machine Learning Scientist to help tackle some of the most complex customer experience problems in the travel domain. You will develop state‑of‑the‑art machine learning and AI solutions to power and enhance the customer experience across highly complex post‑booking recommendations, customer service, and trip management use cases.

You will tackle substantial technical challenges, from inference problems on long‑tail traveler data to multi‑objective optimization in a highly dynamic, operationally complex customer service environment. Your passion for the craft of machine learning, causal inference, and Generative AI will unlock tangible growth for our business by exploiting rich datasets and building effective solutions for travelers and our partners.

This is your opportunity to build core algorithms that help Expedia Group's Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands‑on senior scientist who can independently drive impactful projects, mentor others, and collaborate closely with partners to make travel more seamless for millions of customers and partners worldwide.

In

this role, you will:
Design & Implement ML Solutions
  • Own the end‑to‑end ML lifecycle for medium‑to‑large projects: from problem framing and ideation through research, prototyping, deployment, and post‑launch monitoring.
  • Design robust, scalable ML systems (batch and/or streaming) in partnership with engineering, including data pipelines, feature computation, and model serving.
  • Translate ambiguous business problems into well‑defined ML problems with clear success metrics and validation strategies.
Applied Machine Learning & Data Science
  • Develop, evaluate, and iterate on supervised, unsupervised, and deep learning models for prediction, recommendation, and optimization.
  • Apply causal inference and experimental design (A/B testing) to accurately measure impact and guide decision‑making.
  • Read and apply relevant academic and industry research to improve model architectures, training strategies, and evaluation methods.
  • Contribute to defining best practices for experimentation and modeling within the team; help raise the technical bar for ML development.
Generative AI & Advanced…
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