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Full-Time

Machine Learning Performance Architect

Staff

Posted on 6/27/2024

d-Matrix

d-Matrix

51-200 employees

AI compute platform for datacenters

Hardware
AI & Machine Learning

Senior, Expert

Santa Clara, CA, USA

Requires onsite presence in Santa Clara, California for three days per week.

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Python
Tensorflow
Data Structures & Algorithms
Pytorch
Linux/Unix
Requirements
  • MSEE, Computer Science, Engineering, Math, Physics or related degree + 5 of industry experience, PHD with 3+ Year of industry experience preferred.
  • Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
  • Experience with performance modeling, analysis and correlation (w/ RTL) of GPU/AI Accelerator architectures.
  • Proficient in C/C++ or Python development in Linux environment and using standard development tools.
  • Experience with deep learning frameworks (such as PyTorch, Tensorflow).
  • Experience with inference servers/model serving frameworks (such as Triton, TFServ, KubeFlow,…).
  • Experience with distributed systems collectives such as NCCL, OpenMPI,...
  • Experience with MLOps from definition to deployment including training, quantization, sparsity, model preprocessing, and deployment.
  • Self-motivated team player with a strong sense of ownership and leadership.
  • Prior startup, small team or incubation experience.
  • Work experience at a cloud provider or AI compute / sub-system company.
  • Experience with open-source ML compiler frameworks such as MLIR.
Responsibilities
  • Design space exploration, workload characterization/mapping spanning the data plane as well as control plane in the SoC.
  • Design, model and drive new architectural features to help design next generation hardware.
  • Evaluate performance of cutting edge AI workloads.
  • Build and scale software deliverables in a tight development window.
  • Work with a team of hardware architects to build out the modeling infrastructure and work closely with other software (ML, Systems, Compiler) 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 with 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

$161.5M

Headquarters

Santa Clara, California

Founded

2019

Growth & Insights
Headcount

6 month growth

-11%

1 year growth

3%

2 year growth

243%
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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.

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