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Eridu AI

AI-native networking chips for large clusters

DFT Engineer

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeSaratoga, CA, USA$195k - $250k /yrIn-person

About the Job

Requirements

  • Proficiency with synthesis design constraints, such as SDC.
  • Prior experience with serializers and deserializers.
  • Proficiency with Mentor or Synopsys test tools and synthesis.
  • Knowledge of synthesis, DFT, and simulation computer-aided design tools.
  • Familiarity with logic and physical design principles to drive low-power and higher-performance designs.
  • Fluency in scripting with one or more of Unix, Perl, Python, and Tcl.
  • Good understanding of device physics and experience with deep sub-micron technologies at 7 nm or below.
  • Knowledge of Verilog and SystemVerilog.
  • Prior experience with multiple tape-outs in deep-submicron technologies at 7 nm or below.
  • A master's or bachelor's degree in Electrical Engineering and at least 15 years of experience.

Responsibilities

  • Define the DFT architecture of a multi-chip system-on-chip, involving test-design functions such as scan, BIST, memory repair, and BSD (ACJTAG/DCJTAG).
  • Define and implement OCC.
  • Perform RTL-level and gate-level simulation.
  • Supervise ATPG generation and achieve high coverage goals for scan and at-speed scan.

Desired Qualifications

  • Exposure to advanced DFT techniques such as LBIST and streaming.
  • Prior exposure to EMIB architectures and bridges.

About the Company

Eridu AI

AI-native networking chips for large clusters

Eridu AI designs AI-native networking chips and systems that replace multi-hop optical tiers in large GPU training clusters. Their products place more networking functions on-chip within a redesigned switch stack, which reduces power consumption, cost, and latency as GPU bandwidth scales. This approach differs from traditional Arista-like gear by integrating switching functionality directly into silicon, aiming for highly scalable, energy-efficient networking for hyperscale cloud providers, AI labs, and enterprises running million-GPU-class clusters. The company targets large-scale GPU deployments and seeks to make data-center networking more efficient, scalable, and cost-effective, backed by substantial funding from major investors to support growth and deployment.

Company size
51-200
Company stage
Series A
Total funding
$230M
Headquarters
Saratoga, CA
Founded
2024

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