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MatX

Designs high-throughput AI hardware chips

Mechanical Engineering Lead - AI Rack Scale Systems

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

About the Job

Requirements

  • 15+ years of mechanical engineering experience in server, data center, or AI compute hardware, including hands-on design of mechanical components, sub-assemblies, and assemblies at tray and rack level.
  • Experience leading mechanical teams in designing rack-scale hardware such as compute trays, rack enclosures, or server platforms delivered to OCP Open Rack standards.
  • Experience in volumetric analysis, stack tolerance analysis, and finite element analysis.
  • Experience integrating liquid cooling systems, including cold plates, manifolds, and CDU interfaces, into the overall architecture.
  • Experience generating design for manufacturing and assembly (DFMA) for sheet metal, extrusion, casting, and machining manufacturing processes.
  • Experience in sustainable manufacturing compliance and designing fixtures and test setups for in-process, reliability, and functional testing.
  • Experience leading an ODM/JDM in establishing an assembly line through EVT, DVT, PVT, and mass production phases.

Responsibilities

  • Own mechanical design of AI compute trays, rack enclosures, and rack-scale systems from concept through production, covering structural design, sheet metal, extrusions, castings, and rack-level integration to OCP standards.
  • Direct mechanical engineers on 3D models and 2D drawings for components and assemblies using DFMA-based datum schemes, and run tolerance stack-ups to define IQC, IPQC, and OQC criteria across EVT, DVT, and PVT.
  • Own rack-level integration, including power distribution, cable management, blind-mate connectors, backplane interface, tray insertion and extraction, and packaging design; partner with JDM/ODM to refine the designs.
  • Lead liquid-cooling design and qualification for cold plates, manifolds, CDU interfaces, and QD fittings, from components through L10/L11/L12 validation; partner with thermal engineering on cooling architecture and leak detection.
  • Champion DFM/DFA practices, drive 100% functional test coverage, and guide reliability testing, RMA, and failure analysis.
  • Serve as the lead mechanical point of contact for JDM/ODM, run DFM and qualification reviews, own the BOM and drawings, and author DVT/PVT test plans covering structural, vibration, shock, thermal, and prototype-build testing.
  • Ensure designs meet OCP, ASHRAE, and IEC standards; build and mentor the mechanical/thermal team and manage schedules and risk alongside TPM.

Desired Qualifications

  • Experience with high-power AI accelerator platforms.
  • Prior experience designing for OCP ORV3 or Open Rack Wide (ORW) platforms, or direct involvement in an OCP contribution or workstream.
  • Hands-on experience with direct-to-chip liquid cooling at rack scale, including cold-plate design, manifold routing, QD fitting selection, and CDU integration for high-power racks.
  • Experience taking a mechanical design through high-volume manufacturing with JDM/ODM partners in Taiwan or China, including on-site NPI support.
  • Familiarity with rear door heat exchanger integration as a complement to direct liquid cooling for residual thermal load.

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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