Senior Staff Software Engineer, Search Discover Feed Recommendation Infrastructure

Google Google · Big Tech · Mountain View, CA +1

Senior Staff Software Engineer role focused on leading the architectural work for integrating GenAI capabilities into Google Search's Discover Feed recommendation infrastructure. The role involves evolving the platform into an intelligent, GenAI-powered engine for deep personalization, supporting both offline generation and real-time inference, and optimizing serving latency and infrastructure capacity for billions of users.

What you'd actually do

  1. Lead the architectural work required to bring GenAI capabilities to billions of users.
  2. Drive initiatives to reduce serving latency and optimize infrastructure capacity, ensuring a seamless and efficient experience at scale.
  3. Consolidate our efforts into a unified GenAI platform that supports both offline generation and real-time inference.
  4. Identify optimization and simplification opportunities across multiple work streams with GenAI Infrastructure. Build prototype for proof of concept.
  5. Coordinate development across teams and drive launches.

Skills

Required

  • C++
  • Java
  • Go
  • Python
  • large-scale infrastructure
  • distributed systems
  • networks
  • compute technologies
  • storage
  • hardware architecture
  • design and architecture
  • testing/launching software products

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field
  • data structures and algorithms
  • technical leadership role leading project teams and setting technical direction
  • cross-functional, or cross-business projects

What the JD emphasized

  • GenAI capabilities to billions of users
  • serving latency
  • real-time inference

Other signals

  • GenAI transformation
  • intelligent, GenAI-powered engine
  • deep personalization
  • natural language steering
  • AI-generated content
  • GenAI capabilities to billions of users
  • unified GenAI platform
  • offline generation and real-time inference