Director, Machine Learning Science - Content AI

Expedia•San Jose, CA

2d•$242,000 - $387,000

About The Position

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. Director, Machine Learning Science - Content AI Introduction to the Team: 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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.