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Eridu AI

AI-native networking chips for large clusters

Senior Staff Engineer - Software Engineer, SONiC/SAI

Systems Software EngineeringUpdated on Nov 14
Full-timeSaratoga, CA, USA$210k - $275k /yrIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Science or Electrical and Computer Engineering with 10 or more years of experience, or a Master's degree in Computer Science or Electrical and Computer Engineering with 5 or more years of experience.
  • Proficiency in C, C++, and/or Python.
  • Familiarity with embedded software development and debugging.
  • Deep understanding of networking concepts and protocols, including BGP, TCP/IP, and Ethernet.
  • Hands-on experience developing and maintaining SDKs, preferably for hardware products.
  • Ability to identify, analyze, and resolve complex software issues.
  • Ability to work effectively with cross-functional teams and communicate technical information clearly.

Responsibilities

  • Lead SAI/SONiC SDK development by defining abstraction layers and mapping hardware capabilities to standardized SAI APIs to enable a performant control plane stack.
  • Collaborate with hardware and software engineers to ensure seamless SDK integration and optimal performance.
  • Participate in all stages of the software development lifecycle, from requirements gathering through deployment and maintenance.
  • Create automated tests and tools to verify the quality and functionality of the control plane, including SDKs.

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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