Soc Vision Architect, Silicon, Google Cloud

Google Google · Big Tech · Tel Aviv, Israel +1

This role focuses on architecting the hardware (SoC Vision Architect) for AI/ML applications, specifically Tensor Processing Units (TPUs) and their associated imaging pipelines (ISP, CODECS). The goal is to define custom silicon solutions that power Google's demanding AI/ML workloads, optimizing for power, performance, and area while integrating advanced computational imaging algorithms and potentially deploying neural networks on specialized hardware.

What you'd actually do

  1. Define a flexible imaging pipeline hardware architecture, from the sensor interface (e.g., Mobile Industry Processor Interface (MIPI)) through the ISP, the encoder/decoder, scaling and memory output.
  2. Partner with Google research to transform advanced computational imaging algorithms into high-efficiency hardware logic.
  3. Conduct trade-off analyses between power, performance, and silicon area to meet thermal envelopes and current limitations.
  4. Influence external executive vendor roadmaps, ensuring deep co-optimization between their future products and Google’s custom silicon.
  5. Lead collaboration across Architecture, Register-Transfer Level (RTL), Physical Design and Validation teams.

Skills

Required

  • SoC architecture
  • imaging pipeline design
  • ISP architecture
  • video CODECS
  • CMOS image sensor architecture
  • architecture specifications

Nice to have

  • TPU architecture
  • AI/ML hardware acceleration
  • computational imaging algorithms
  • deploying neural networks on specialized hardware
  • MIPI
  • DRAM/LPDDR
  • hardware/software interfaces

What the JD emphasized

  • 15 years of experience in SoC architecture, specifically focusing on imaging (JPEG), video (H.264, H.265, AV1) and Image Signal Processor (ISP).
  • Experience in Complementary Metal Oxide Semiconductor (CMOS) image sensor architecture.
  • Experience in writing architecture specifications.

Other signals

  • TPU architecture
  • AI/ML hardware acceleration
  • computational imaging algorithms
  • deploying neural networks on specialized hardware