Internship

Analog Mixed-Signal Intern

Posted on 11/12/2024

d-Matrix

d-Matrix

51-200 employees

AI compute platform for datacenters

Hardware
AI & Machine Learning

Santa Clara, CA, USA

Category
Electronics Design Engineering
Embedded Systems Engineering
Electrical Engineering
Requirements
  • Master or PhD with experiences in mixed-signal circuit design (transceiver, data converter, PLL, SerDes, Power management, ALU designs) are highly preferred.
Responsibilities
  • Design Building blocks and Architectural investigation of Die-to-Die (D2D) interconnect
  • Design Digital-In-Memory compute building blocks
  • Responsibilities include schematic design and layout

d-Matrix focuses on improving the efficiency of AI computing for large datacenter customers. Its main product is the digital in-memory compute (DIMC) engine, which combines computing capabilities directly within programmable memory. This design helps reduce power consumption and enhances data processing speed while ensuring accuracy. d-Matrix differentiates itself from competitors by offering a modular and scalable approach, utilizing low-power chiplets that can be tailored for different applications. The company's goal is to provide high-performance, energy-efficient AI inference solutions to large-scale datacenter operators.

Company Stage

Series B

Total Funding

$149.8M

Headquarters

Santa Clara, California

Founded

2019

Growth & Insights
Headcount

6 month growth

11%

1 year growth

-3%

2 year growth

219%
Simplify Jobs

Simplify's Take

What believers are saying

  • Raised $110 million in Series B funding, indicating strong investor confidence.
  • Launch of 'Corsair' positions d-Matrix as a competitor to Nvidia.
  • Jayhawk II silicon enhances AI inference efficiency for large language models.

What critics are saying

  • Faces competition from established players like Nvidia and emerging startups.
  • Rapid AI innovation may lead to technological obsolescence for d-Matrix.

What makes d-Matrix unique

  • d-Matrix integrates compute into programmable memory for enhanced AI efficiency.
  • Their DIMC engine offers a unique approach to AI inference in data centers.
  • The modular chiplet design allows customization for various AI applications.

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