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Director, Machine Learning Science - Content AI

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Expedia Group
Full Time position
Listed on 2026-04-20
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

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.

Are you ready to lead the revolution in how travel content is generated, moderated, and delivered? Expedia Group is seeking a Director of Machine Learning Science to lead our Content AI strategy and execution.

In this pivotal role, you will move beyond traditional ML applications to architect the next generation of our Content Engine. You will leverage Large Language Models (LLMs), Multimodal Modality, Agentic Workflow to ensure that every image, review, property description, and video is not only relevant but inspiring, safe, and hyper-personalized.

In this role, you will:
  • Define the Content AI Strategy:
    Establish the technical roadmap and OKRs for the Machine Learning systems that power Content Generation, Content Moderation, and Content Relevance across our global ecosystem.
  • Lead AI Innovation:
    Spearhead the deployment of cutting-edge AI solutions (LLMs, Diffusion Models) to automate content creation (text, image, video) and summarization, enhancing discovery on both app and web platforms.
  • Pioneer Agentic Workflows:
    Drive the research and development of autonomous AI Agents capable of reasoning over vast content repositories to answer complex traveler queries and perform multi-step planning tasks.
  • Master Content Relevance & Safety:
    Oversee the development of models that rank and personalize content to improve conversion and loyalty, while simultaneously building robust automated moderation pipelines to ensure brand safety, trust, and quality at scale.
  • Bridge the Gap between Research & Product:
    Prioritize efforts between foundational platform migration/optimization and cutting-edge experimentation with new GenAI features.
  • Influence & Collaborate:
    Foster cross-functional partnerships with Product, Engineering, Legal, and Supply teams to integrate AI-generated content into the core user experience seamlessly.
  • Build a World-Class Team:
    Recruit, mentor, and manage a high-performing team of Applied Scientists and AI Engineers, fostering a culture of technical excellence and rapid experimentation.
Minimum Qualifications:
  • Graduate degree (PhD preferred) in Computer Science, Artificial Intelligence, Computational Linguistics; or relevant equivalent experience.
  • 12+ years of experience in Machine Learning Science with a specific focus on NLP, Computer Vision, or Recommender Systems.
  • 5+ years of people management experience, with a track record of leading high-performing science teams in a tech-first environment.
  • Hands‑on experience with Generative AI technologies (e.g., Transformer architectures, LLMs like LLaMA/GPT, RAG pipelines, PEFT/LoRA fine‑tuning). You understand the challenges of hallucination, latency, and cost optimization.
  • Proven experience in the Content ML/AI space, specifically regarding Content Understanding, Moderation, Generation and Relevance, creating rich and immersive user experiences.
  • A proven track record of taking high-risk, high-reward ML projects from proof‑of‑concept to large-scale production serving millions of users.
Preferred Qualifications:
  • Agentic AI

    Experience:

    Experience building and deploying Agentic workflows. You have experience with agents that demonstrate tool use, planning, and reasoning capabilities.
  • Ability to translate complex AI concepts into clear business value for executive stakeholders.
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