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d-Matrix

Delivers memory-integrated AI compute platforms

Director Quality and Reliability Engineering - AI Hardware

Quality EngineeringConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA$195k - $285k /yr

About the Job

Requirements

  • At least 15 years of experience in hardware quality and reliability engineering, including at least 5 years leading multidisciplinary teams.
  • A Bachelor of Science or Master of Science in Electrical Engineering, Mechanical Engineering, or a related engineering field.
  • Deep exposure to server-class systems, AI accelerators, or data center hardware.
  • A proven track record of building or scaling a Quality Management System through high-volume ramps.
  • Hands-on experience across supplier, manufacturing, and customer quality, including original design manufacturers and contract manufacturers.
  • Component engineering experience in qualification, Approved Vendor List management, second sourcing, and lifecycle management.
  • Command of reliability fundamentals, including mean time between failures, acceleration models, reliability demonstration testing, ongoing reliability testing, and system-, rack-, and cluster-level availability, as well as quality tools including 8D, 5-Why, failure mode and effects analysis, statistical process control, and design of experiments.
  • ISO 9001 lead auditor experience or equivalent.
  • Familiarity with Arena or Agile product lifecycle management systems.
  • Ability to represent quality effectively with customers, suppliers, and internal stakeholders.

Responsibilities

  • Own the Quality Management System and audit readiness, aligned to ISO 9001 or equivalent.
  • Own product quality and reliability engineering, including qualification, reliability demonstration testing, mean time between failures, ongoing reliability testing, and fault-tolerant design.
  • Own supplier quality across original design manufacturers, contract manufacturers, and component suppliers.
  • Own manufacturing quality at original design manufacturer and contract manufacturer sites, including process control, yield, defects per million parts, and shipment readiness.
  • Own customer quality, including returns and material authorizations, reverse logistics, failure analysis, and customer escalations.
  • Own component engineering for board-level products and above, including qualification, Approved Vendor List governance, and second sourcing.
  • Define quality metrics and executive reporting, with independent reporting to leadership.
  • Set quality strategy, standards, and outcomes in collaboration with Engineering, Manufacturing, Test, and Supplier and Partner Management.
  • Build and scale the Quality Management System, including Control Plans, Work Instructions, and corrective and preventive action governance, across ASIC, card, server, rack, and cluster-level products.
  • Design and run returns and material authorization, reverse logistics, and failure analysis processes with closed-loop feedback into design and manufacturing.
  • Drive reliability programs and fault-tolerant design to meet AI data center availability requirements.
  • Establish supplier and manufacturing quality programs across partners, including audits, process controls, and new product introduction build readiness.
  • Lead component engineering for board-level products and above, including qualification, second-source programs, and lifecycle management.
  • Define quality key performance indicators and dashboards for yield, defects per million parts, returns and material authorization rate, mean time between failures, and corrective and preventive action closure; report independently to executive leadership.
  • Represent quality in product release and shipment readiness, customer audits, and escalations; build, hire, and develop the quality organization for volume shipments and rack-scale solutions.

Desired Qualifications

  • ASQ Certified Quality Engineer or Certified Reliability Engineer credentials.

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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