Staff Software Engineer, Beyond Live, Deepmind

Google Google · Big Tech · New York, NY +3

Staff Software Engineer at Google DeepMind focused on building the serving platform and core orchestration infrastructure for next-generation conversational AI agents. The role involves designing and implementing systems for agent testing, developing test problems in simulators, creating visualizations, building leaderboards, and testing algorithms on robots. Key responsibilities include optimizing end-to-end latency, managing TPU capacity, and building bidirectional streaming APIs for multimodal inference, all while collaborating with researchers to translate AI breakthroughs into production services at Google scale.

What you'd actually do

  1. Design and implement multi-threaded and multi-system orchestration to manage real-time user-model interactions.
  2. Optimize end-to-end latency using speculative decoding, audio/video pacing, flow control.
  3. Manage TPU capacity by tuning model exports and estimating launch footprints to guarantee service reliability.
  4. Build bidirectional streaming APIs for multimodal inference.

Skills

Required

  • software development
  • software design and architecture
  • testing and launching software products
  • C++

Nice to have

  • evaluating and vetting technical designs, feature requests, and code implementations
  • navigating ambiguity
  • driving alignment on technical direction
  • translating experimental features into concrete engineering plans
  • pivoting and adapting to rapid changes
  • collaboration across research and product client teams
  • AI agents
  • 2D and 3D games
  • physics simulators
  • graphical visualization
  • competitive agent leaderboards
  • robots

What the JD emphasized

  • building the world's first general-purpose learning agent
  • design and build the serving platform and core orchestration infrastructure
  • real-time, low-latency, multimodal, and bidirectional communication
  • systems issues in C++ (mostly), from low-latency streaming and audio/video tokenization to proactive orchestration and multiple-model (e.g., talker/thinker) interactions
  • build the foundational platform that makes AI agents feel truly conversational and alive

Other signals

  • building foundational platform for conversational AI
  • real-time, low-latency, multimodal, and bidirectional communication
  • AI agents feel truly conversational and alive