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Principal ML Scientist

Job in Spokane, Spokane County, Washington, 99254, USA
Listing for: Traveltechessentialist
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

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.

Principal Machine Learning Scientist, GenAI

This role sits within Expedia’s Traveler & Partner Service Platform (TPSP) Product & Technology organization, which builds the core capabilities and experiences that power customer service across the Expedia ecosystem. TPSP enables both travelers and partners to receive high-quality, efficient service through a combination of human support and AI-powered experiences.

We are looking for a highly influential science leader to help drive the technical strategy and execution for LLM-powered AI Agent servicing for Expedia travelers and partners, with strong traditional ML based personalization skills along with Agentic AI skillsets within the servicing domain. This role will define and lead the transformation towards scalable, voice and chat based self-service experiences powered by AI agents—reducing customer effort while improving resolution speed, consistency, customer satisfaction, and operational efficiency.

As a Principal Machine Learning Scientist, you will partner with key senior leaders to architect the long-term science vision for customer AI servicing, drive complex cross-functional execution, and build a culture of scientific thinking, research and innovation in the organization. You will operate as an indispensable leader, shaping how agentic AI is designed, governed, measured, and scaled across TPSP.

What you’ll do
  • Define and lead the ML strategy for one or more complex product or platform areas (e.g., personalization, search & recommendations, pricing, fraud/risk, or generative AI–powered experiences).
  • Formulate ill-defined business problems into well-posed ML problems, selecting appropriate modeling approaches and success metrics.
  • Design and implement state-of-the-art ML models (e.g., deep learning, representation learning, causal inference, bandits, LLM/GenAI where appropriate) and own them through production.
  • Partner closely with engineering to product ionize models, improve data and feature pipelines, and ensure reliability, latency, and scalability requirements are met.
  • Lead experiment design and evaluation
    , including A/B tests and offline evaluations; drive decisions with rigorous statistical analysis.
  • Proactively identify opportunities where ML can unlock new customer and business value
    , build business cases, and influence product and leadership roadmaps.
  • Establish and champion best practices for model development, evaluation, monitoring, and responsible AI (fairness, robustness, privacy, and safety).
  • Provide technical leadership and mentorship to other ML scientists, data scientists, and ML engineers through design reviews, pairing, and informal coaching.
  • Communicate complex technical topics in clear, concise ways to executives, product leaders, and non-technical stakeholders
    , influencing direction across teams and organizations.
  • Collaborate with platform and infra teams to evolve ML tools, feature stores, experimentation platforms, and model monitoring capabilities.
Minimum Qualifications
  • Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering
    , or a related technical field; or equivalent practical experience.
  • 10+ years of experience in applied ML / data science, including significant experience owning production models in complex domains.
  • Deep expertise in machine learning algorithms and…
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