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MatX

Designs high-throughput AI hardware chips

Lead Software Engineer - Kernels

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeMountain View, CA, USA

About the Job

Requirements

  • At least 2 years of engineering team management experience.
  • At least 7 years of experience working directly within engineering teams.
  • A Bachelor's degree in Computer Science or an equivalent degree.
  • Experience optimizing software for specialized hardware using techniques such as parallelism, SIMD programming, C, assembly-level optimization, or GPU/CUDA programming.
  • Experience with at least one of assembly, C++, C, Zig, or Rust.
  • Ability to navigate ambiguity, manage escalations, and align stakeholders around infrastructure decisions.
  • Communication and collaboration skills, including translating complex technical trade-offs to founders and stakeholders.

Responsibilities

  • Manage, mentor, and build a team of kernel engineers and software developers.
  • Design and optimize kernels that interface directly with the company's hardware.
  • Partner with the ML Research and Hardware Engineering teams.
  • Provide expertise and guidance on hardware architecture from a programmer's perspective to ensure seamless integration with the software stack.
  • Actively contribute code by designing and implementing high-performance compute kernels for specialized AI hardware.
  • Set technical direction and execute for the Kernel team.
  • Partner with the ML team to maximize output and improve diagnostic tools.
  • Collaborate with hardware teams to co-design next-generation AI architectures.

Desired Qualifications

  • Experience implementing kernels for ML models such as Transformers.
  • Experience using and implementing distributed parallelism techniques such as AllReduce, AllToAll, data parallelism, and tensor parallelism.
  • Familiarity with how compilers work.

About the Company

MatX

Designs high-throughput AI hardware chips

MatX builds high-throughput AI accelerators for large language models. Its main product is a dedicated chip where every transistor is optimized for running large neural networks, aiming to deliver strong performance for training and inference of LLMs. The company also develops the surrounding software stack, including compilers, to make the hardware easy to program for ML engineers (e.g., through JAX-based workflows). Unlike general-purpose processors, MatX focuses on specialization and full-stack optimization from silicon to software. Its goal is to enable organizations with substantial AI workloads to scale efficiently by providing powerful, purpose-built hardware and the compatible software tools they need to deploy and optimize large models.

Company size
51-200
Company stage
Series B
Total funding
$604.9M
Headquarters
Mountain View, CA
Founded
2022

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