Director, Machine Learning Science - Content AI

Expedia Expedia · Hospitality · London, USA, United Kingdom

Director of Machine Learning Science to lead Content AI strategy and execution, focusing on LLMs, Multimodal Modality, and Agentic Workflows for content generation, moderation, and relevance. The role involves defining strategy, leading AI innovation with LLMs and Diffusion Models, pioneering agentic workflows, mastering content relevance and safety, bridging research and product, influencing cross-functional teams, and building a world-class team. Requires a PhD or equivalent experience, 12+ years in ML Science (NLP, CV, Recommender Systems), 5+ years of people management, and hands-on experience with Generative AI technologies and content ML/AI.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Bridge the Gap between Research & Product: Prioritize efforts between foundational platform migration/optimization and cutting-edge experimentation with new GenAI features.

Skills

Required

  • 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).
  • 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 have

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

What the JD emphasized

  • Content AI Strategy
  • Content Generation
  • Content Moderation
  • Content Relevance
  • LLMs
  • Diffusion Models
  • Agentic Workflows
  • AI Agents
  • hallucination
  • latency
  • cost optimization
  • Content ML/AI
  • Agentic AI Experience
  • tool use
  • planning
  • reasoning capabilities

Other signals

  • LLMs
  • Multimodal
  • Agentic Workflow
  • Content Generation
  • Content Moderation
  • Content Relevance
  • Diffusion Models
  • Summarization
  • Personalization
  • Brand Safety
  • Trust
  • Quality
  • GenAI Features
  • User Experience
  • NLP
  • Computer Vision
  • Recommender Systems
  • Hallucination
  • Latency
  • Cost Optimization