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MatX

Designs high-throughput AI hardware chips

Mechanical Engineer - AI Rack Scale Systems

Design EngineeringUpdated on Nov 14
Full-time

About the Job

Requirements

  • At least 5 years of mechanical engineering experience in server, data center, or AI compute hardware.
  • Experience designing rack-scale hardware such as compute trays, rack enclosures, or server platforms.
  • Familiarity with OCP Open Rack standards.
  • Experience with liquid cooling systems such as cold plates, manifolds, or CDU interfaces.
  • Proficiency in 3D CAD (SolidWorks or equivalent) and GD&T.
  • Familiarity with sheet metal, extrusion, casting, and machining manufacturing processes.

Responsibilities

  • Develop AI compute trays, rack enclosures, and mechanical assemblies in accordance with OCP Rack specifications.
  • Produce 3D models and 2D drawings at component, sub-assembly, and assembly levels, and maintain the mechanical bill of materials, drawing packages, and GD&T documentation throughout NPI stages.
  • Design and integrate liquid cooling hardware including cold plates, manifolds, quick-disconnect fittings, and CDU-to-rack interfaces.
  • Support mechanical integration of compute trays into rack systems across power, liquid cooling, cabling, and connector interfaces.
  • Carry out tolerance stack-up analysis at multiple levels, from package through rack, to confirm proper fit and straightforward assembly.
  • Take a hands-on role in EVT, DVT, and PVT prototype builds, bring-up, and debug.
  • Apply DFM/DFA principles and contribute to design reviews with JDM/ODM manufacturing partners.

Desired Qualifications

  • Experience with high-power AI accelerator platforms.
  • Hands-on cold plate manufacturing experience.
  • Experience working with JDM/ODM partners.
  • Knowledge of liquid cooling reliability standards and leak testing methodologies.

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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