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Full-Time

Design Verification Engineer – Principal

Confirmed live in the last 24 hours

d-Matrix

d-Matrix

51-200 employees

AI compute platform using in-memory computing

Data & Analytics
Hardware
AI & Machine Learning

Senior, Expert

Santa Clara, CA, USA

Category
Embedded Systems Engineering
Electrical Engineering
Requirements
  • BS in Electrical Engineering, Computer Science or related field with 15+ years of Industry experience or MS Electrical Engineering, Computer Science or related field preferred with 12+ years industry experience.
  • Experience in SoC verification cycle from architecture to tape out to bring up.
  • Good knowledge of verification methodologies such as UVM/OVM etc.
  • Hands on ASIC-SoC Design verification tests and debug experience.
  • Fluency with SystemVerilog randomization constraints, coverage, and assertions methodology.
  • Good problem-solving skills, and the passion to take on challenges (particularly in AI domain).
  • Good experience with SystemVerilog, and verification methodology (UVM/OVM/VMM).
  • Passionate about AI and thriving in a fast-paced and dynamic startup culture.
Responsibilities
  • Work on a path breaking architecture with a highly experienced team that knows what it takes to build a successful business.

d-Matrix is developing a unique AI compute platform using in-memory computing (IMC) techniques with chiplet level scale-out interconnects, revolutionizing datacenter AI inferencing. Their innovative circuit techniques, ML tools, software, and algorithms have successfully addressed the memory-compute integration problem, enhancing AI compute efficiency.

Company Stage

Series B

Total Funding

$161.5M

Headquarters

Santa Clara, California

Founded

2019

Growth & Insights
Headcount

6 month growth

-15%

1 year growth

85%

2 year growth

223%
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Simplify's Take

What believers are saying

  • Securing $110 million in Series B funding positions d-Matrix for rapid growth and technological advancements.
  • Their Jayhawk II silicon aims to solve critical issues in AI inference, such as cost, latency, and throughput, making generative AI more commercially viable.
  • The company's focus on efficient AI inference could attract significant interest from data centers and enterprises looking to deploy large language models.

What critics are saying

  • Competing against industry giants like Nvidia poses a significant challenge in terms of market penetration and customer acquisition.
  • The high dependency on continuous innovation and technological advancements could strain resources and lead to potential setbacks.

What makes d-Matrix unique

  • d-Matrix focuses on developing AI hardware specifically optimized for Transformer models, unlike general-purpose AI chip providers like Nvidia.
  • Their digital in-memory compute (DIMC) architecture with chiplet interconnect is a first-of-its-kind innovation, setting them apart in the AI hardware market.
  • Backed by major investors like Microsoft, d-Matrix has the financial support to challenge established players like Nvidia.