Full-Time

Software Engineer – Senior Staff

Kernels

Posted on 7/27/2024

d-Matrix

d-Matrix

51-200 employees

AI compute platform for datacenters

Enterprise Software
AI & Machine Learning

Senior

Santa Clara, CA, USA

Hybrid position requiring onsite presence in Santa Clara, CA for 3 days per week.

Category
Embedded Engineering
Software QA & Testing
Software Engineering
Required Skills
Python
CUDA
Data Structures & Algorithms
C/C++
FPGA
Linux/Unix
Requirements
  • MS or PhD in Computer Engineering, Math, Physics or related degree with 5+ years of industry experience.
  • Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
  • Proficient in C/C++ and Python development in Linux environment and using standard development tools.
  • Experience implementing algorithms in high-level languages such as C/C++ and Python.
  • Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CuDA, etc.
  • Experience in implementing operators commonly used in ML workloads - GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc.
  • Experience with development for embedded SIMD vector processors such as Tensilica.
  • Self-motivated team player with a strong sense of ownership and leadership.
Responsibilities
  • You will be responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware.
  • You possess experience building software kernels for HW architectures.
  • You possess a very strong understanding of various hardware architectures and how to map algorithms to the architecture.
  • You understand how to map computational graphs generated by AI frameworks to the underlying architecture.
  • You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade-off various aspects of hardware-software co-design.
  • You can build and scale software deliverables in a tight development window.
  • You will work with a team of compiler experts to build out the compiler infrastructure, working closely with other software (ML, Systems) and hardware (mixed signal, DSP, CPU) experts in the company.

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. Unlike many competitors, d-Matrix offers 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

-2%

2 year growth

219%
Simplify Jobs

Simplify's Take

What believers are saying

  • Growing interest in DIMC technology aligns with d-Matrix's core product offerings.
  • Rising demand for energy-efficient AI solutions benefits d-Matrix's power-efficient platforms.
  • Recent funding positions d-Matrix to capitalize on the growing use of AI in generative applications.

What critics are saying

  • Increased competition from Nvidia, AMD, and Intel could impact d-Matrix's market share.
  • Rapid AI innovation may lead to obsolescence if d-Matrix fails to keep pace.
  • Potential regulatory changes in AI technology could impose new compliance costs.

What makes d-Matrix unique

  • d-Matrix's DIMC engine integrates compute into memory, enhancing AI inference efficiency.
  • The company's chiplet-based design offers modular and scalable AI compute solutions.
  • d-Matrix focuses on power-efficient AI platforms, addressing critical datacenter power consumption issues.

Help us improve and share your feedback! Did you find this helpful?

INACTIVE