Senior Tpu Rtl Design Engineer, Networking, Inter-chip Interconnects

Google Google · Big Tech · Sunnyvale, CA +1

Senior engineer to design and develop RTL for Google's next-generation Tensor Processing Units (TPUs), focusing on inter-chip interconnects for AI and networking accelerators. This role involves microarchitecture, RTL design, implementation, and collaboration with system architects and verification teams to ensure high-performance, power-efficient silicon solutions for AI workloads.

What you'd actually do

  1. Lead the microarchitecture and RTL execution to deliver high-performance network design components which meet strict power, performance and area (PPA) goals and satisfy established coding and quality guidelines.
  2. Collaborate with system architects and software/firmaware teams to ensure alignment between system and IP requirements.
  3. Own the complete RTL lifecycle from initial microarchitecture, coding and documentation to ensuring sign-off readiness for Lint, CDC, and synthesis.
  4. Collaborate with the Verification team to develop test plans, debug RTL, and ensure functional correctness.
  5. Work closely with the Physical Design team to meet timing, area, power, and manufacturability requirements.

Skills

Required

  • high-performance ASIC design
  • architecting or designing RTL solutions for digital systems
  • high-speed interconnects
  • networking IP across one or more layers (MAC, L2, or PHY)

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture
  • 7 years of experience in high-performance ASIC design
  • IEEE networking standards and applications
  • scripting languages (e.g., Tcl, Python or Perl)
  • familiarity with one or more industry-standard tools for CDC, RDC, RTL Linting, or LEC
  • digital design fundamentals, including synchronous and asynchronous logic, state machines, and bus protocols

What the JD emphasized

  • custom silicon solutions
  • AI acceleration
  • high-speed interconnect subsystems
  • challenging technical problems at the forefront of AI hardware

Other signals

  • TPU design
  • AI/ML hardware acceleration
  • inter-chip interconnects
  • ASIC/SoC hardware for AI accelerators