Staff Machine Learning Engineer - Search

Warner Bros Discovery Warner Bros Discovery · Media · San Francisco, CA +4 · Technology

Staff Machine Learning Engineer for Search & Personalization at Warner Bros. Discovery, focusing on HBO Max. The role involves leading the design and evolution of ML/AI driven search algorithms, from retrieval and ranking to personalization and experimentation. It requires deep expertise in search/relevance systems, technical leadership, and driving the end-to-end ML lifecycle in a large-scale production environment.

What you'd actually do

  1. Lead the design and development of large-scale model driven search algorithms including retrieval, ranking, and query understanding
  2. Define and evolve the technical strategy for search, balancing relevance, latency, and scalability
  3. Drive end-to-end ML systems: data pipelines, feature engineering, model training, experimentation, and serving
  4. Partner closely with product, data, and infrastructure teams to shape and execute on the search roadmap and user experience
  5. Mentor engineers and data scientists and raise the bar on algorithm development, system design, ML and engineering practices

Skills

Required

  • Python
  • SQL
  • distributed systems
  • cloud platforms (AWS/GCP/Azure)
  • data pipelines
  • feature engineering
  • model training
  • experimentation
  • serving
  • search and/or ranking algorithms
  • large-scale ML systems in production
  • technical direction
  • influence across teams
  • online experimentation
  • metrics-driven development

Nice to have

  • Java
  • Go
  • recommender systems
  • personalization
  • NLP techniques
  • vector search / ANN
  • streaming platforms
  • marketplace platforms
  • content discovery platforms

What the JD emphasized

  • deep expertise in search/relevance systems
  • strong technical leadership
  • Lead the design and development of large-scale model driven search algorithms
  • Define and evolve the technical strategy for search
  • Drive end-to-end ML systems
  • search roadmap
  • lead technical direction and influence across teams
  • online experimentation and metrics-driven development

Other signals

  • end-to-end ML systems
  • large-scale model driven search algorithms
  • online experimentation and metrics-driven development