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d-Matrix

Delivers memory-integrated AI compute platforms

Staff Software Engineer - SIMD Kernels

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA$190k - $300k /yr

About the Job

Requirements

  • An MS or PhD in computer engineering, mathematics, physics, or a related degree, with at least 5 years of industry experience.
  • A strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
  • Proficiency in C/C++ and Python development in a Linux environment using standard development tools.
  • Experience implementing algorithms in C/C++ and Python.
  • Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, or AI accelerators, using libraries such as CUDA.
  • Experience implementing operators commonly used in machine learning workloads, including GEMMs, convolutions, softmax, layer normalization, and pooling.
  • Experience building software kernels for modern hardware architectures and understanding how to map algorithms and AI-framework computational graphs onto those architectures.
  • Comfort working across the full toolchain and navigating hardware-software co-design trade-offs.
  • Ability to deliver and scale high-quality software in a fast-moving development environment.

Responsibilities

  • Help productize the software stack for the AI compute engine.
  • Develop, enhance, and maintain software kernels for machine learning operators, such as softmax, layer normalization, and activation functions, for next-generation AI hardware.
  • Build solutions that make the SDK intuitive for developers to use and analyze performance.

Desired Qualifications

  • Prior startup, small-team, or incubation experience.
  • Experience with machine learning frameworks such as TensorFlow and/or PyTorch.
  • Experience working with machine learning compilers and algorithms such as MLIR, LLVM, TVM, or Glow.
  • Experience with a deep learning framework such as PyTorch or TensorFlow and machine learning models for computer vision, natural language processing, or recommendation.
  • Experience developing for embedded SIMD vector processors such as Tensilica.
  • Work experience at a cloud provider or AI compute/subsystem company.

About the Company

d-Matrix

Delivers memory-integrated AI compute platforms

d-Matrix provides scalable AI compute platforms for large datacenters with a focus on energy efficiency. Its core offering, the digital in-memory compute (DIMC) engine, places compute directly in programmable memory and uses a fabric of low-power, modular chiplets plus software to optimize AI inference. It differentiates itself by combining memory-integrated computation with a modular, chiplet-based design that reduces power use and data movement for high-volume workloads. The goal is to help large datacenters run AI workloads more efficiently at scale through customizable, energy-efficient compute solutions.

Company size
201-500
Company stage
Series C
Total funding
$429M
Headquarters
Santa Clara, CA
Founded
2019

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