Senior AI System Engineer

Google Google · Big Tech · New Taipei, Banqiao District, New Taipei City, Taiwan +1

Senior AI System Engineer role focused on influencing Tensor SoC architecture for AI/ML workloads on Pixel devices. This involves cross-functional collaboration with SW/HW architects and research teams to optimize for Power, Performance, and Area (PPA) trade-offs, enabling advanced Generative AI experiences. The role requires a data-driven approach using profiling, simulation, and modeling to define future SoC architectures and system design documentation.

What you'd actually do

  1. Influence Tensor SoC architecture decisions for PPA working cross-functionally with SW/HW architects, design teams, and research teams to enable the industrial best user experience on Pixel phone devices empowered by the latest and the most advanced Generative AI technologies provided by Google research.
  2. Leverage a data driven approach through profiling, simulation and modeling, drive consensus around architectural decisions across the entire silicon organization to solve system design problems.
  3. Be the primary owner of the architecture specifications, system design documentation, workload analysis, modeling and projection to influence and define future SoC architecture.

Skills

Required

  • 8 years of experience with computer architecture concepts, including micro architecture, cache hierarchy, pipelining, and memory subsystems.
  • 3 years of experience working with mobile or embedded SoCs architecture or use case system design.

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science.
  • 5 years of experience working with mobile or embedded SoCs related to system design to improve use case level power and performance.
  • Experience driving system architecture decisions across SW/HW teams within an organization to build up the consensus and translate ideas into architecture specifications.
  • Experience with android architecture, mobile SoC architecture, ML architecture, computer architecture, PPA trade-offs.
  • Knowledge of interactions between software and HW IP blocks, general and special purpose compute units.

What the JD emphasized

  • custom silicon solutions
  • Tensor SoC
  • mobile SoC AI/ML workloads analysis
  • Pixel devices
  • Generative AI technologies
  • computer architecture concepts
  • mobile or embedded SoCs architecture

Other signals

  • custom silicon solutions
  • Tensor SoC
  • mobile SoC AI/ML workloads analysis
  • Pixel devices
  • Generative AI technologies