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Neurophos

Optical metasurface AI accelerators

Physical Design / Implementation Lead

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Track record leading physical design or implementation on large, complex SoCs through tapeout, as a back-end lead on a large SoC or through an equivalent combination of synthesis, timing closure, power, and physical-verification ownership at a senior level.
  • Hands-on experience on advanced nodes; FinFET-class node experience from 7nm to 3nm is required.
  • Deep power and clock design experience at scale, ideally from CPU-class or very large SoC work.
  • A track record of leading and growing a team.

Responsibilities

  • Own physical design and implementation end-to-end, from synthesis through tapeout, on leading-edge process nodes.
  • Optimize and automate the synthesis flow, and lead the intake of new process technology as new nodes are brought on.
  • Optimize and automate the timing closure process at the block and subsystem level.
  • Design and optimize power and clock architecture distribution networks.
  • Own the integration of analog and mixed-signal components into the digital implementation flow, building the process and working relationship between analog and digital teams.
  • Own physical verification and IP/library management for the digital design organization.
  • Build and lead a physical design team by hiring, ramping, and managing engineers as the group scales.
  • Work closely with RTL/DV, Analog, and other team leads on cross-functional flow and schedule decisions.

Desired Qualifications

  • TSMC N3 experience is strongly preferred.
  • Experience integrating analog/mixed-signal blocks into a digital implementation flow.
  • Cadence toolchain experience.

About the Company

Neurophos

Optical metasurface AI accelerators

Neurophos designs AI accelerator chips built with optical metasurfaces and silicon photonics to deliver high-density, energy-efficient AI computation for data centers. Its processors are designed to shrink optical components by about 8000x, increasing compute power per dollar spent and reducing both capital and operating expenditures. The product works by using optical processing techniques that handle AI inference workloads more efficiently than traditional GPUs or electronic AI accelerators, enabling faster throughput with lower power use. Neurophos differentiates itself by combining optical metasurfaces with silicon photonics to achieve higher density and energy efficiency, targeting data centers and enterprises that need scalable, cost-sensitive AI inference. The company aims to reshape the AI landscape by offering faster, denser, and more energy-efficient AI computation while lowering the total cost of ownership for data centers.

Company size
51-200
Company stage
Series A
Total funding
$117.2M
Headquarters
Austin, TX
Founded
2020

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