Contract Site Reliability Engineer — AI Accelerator Infrastructure

Posted Yesterday
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Santa Clara, CA, USA
Hybrid
155K-235K Annually
Mid level
Artificial Intelligence • Machine Learning • Software
The Role
Contract role to perform hands-on data center and lab infrastructure tasks: rack/stack/cable servers, hardware bring-up (BIOS/firmware/OS), replace components, maintain ESD-compliant labs, manage asset inventory via DCIM, troubleshoot hardware/power/network incidents, document SOPs and runbooks, and coordinate with SREs and engineering teams.
Summary Generated by Built In

At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration.

We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution.  Ready to come find your playground? Together, we can help shape the endless possibilities of AI. 

d-Matrix designs purpose-built AI inference silicon. Our unified infrastructure team, SRE engineers, DevOps engineers, and data center & lab technicians own the physical and virtual layer that every engineering team depends on. As a DC & lab technician, you are the hands and feet of that team: racking servers, running cables, executing hardware bring-ups, and keeping lab environments in the precise, audit-ready state that high-velocity silicon and software development demands.


About the Role

This is a one-year contract with potential for a full-time conversion. This is an ownership role, not a ticket executor role. You operate independently, document what you build, and escalate with precision when something needs engineering attention.

 
What You Will DoPhysical Infrastructure & Hardware Bring-Up
  • Rack, stack, cable, and decommission servers, PDUs, network gear, and storage in on-premises labs and colocation facilities.

  • Execute hardware bring-up for d-Matrix AI-accelerated systems and validation test benches, including BIOS configuration, firmware validation, and OS installation (Linux primary).

  • Replace and upgrade components: PCIe cards, NICs, storage, memory, and accelerator hardware across multiple server generations.

  • Maintain lab spaces in organized, ESD-compliant, and audit-ready condition at all times.

 
Asset Management & Inventory
  • Own accurate asset tracking and inventory records using DCIM tools (NetBox, Jira, or equivalent); every piece of hardware is accounted for with the current configuration state.

  • Coordinate equipment moves between lab, staging, and colocation; manage shipping, receiving, and RMA workflows.

  • Track hardware lifecycle status: warranty, EOL, refresh schedules, and spare parts inventory.

 
Troubleshooting & Incident Support
  • Diagnose and resolve hardware failures, power and thermal issues, and network connectivity problems — escalating to SRE engineers with clear documentation and reproduction steps.

  • Serve as the first physical responder for infrastructure incidents requiring hands-on intervention in lab or colo environments.

  • Document all troubleshooting actions in the team’s ticketing and knowledge base systems, contributing to runbooks that reduce repeat escalations.

 
Documentation & Collaboration
  • Write and maintain SOPs, rack diagrams, and cabling guides clear enough for a new technician to execute without shadowing.

  • Communicate issues and status across hardware, software, SRE, and silicon validation teams professionally and with precision.

  • Support parallel workstreams as silicon development programs evolve; operate independently when SREs are heads-down on engineering work.

 
What You Will BringMinimum Qualifications
  • 3+ years in data center operations, hardware validation, or systems technician roles, hands-on with real servers.

  • Proven rack-and-stack experience: physical server installation, PDU and patch panel cabling, rack power planning, and cable management to professional standards.

  • Hardware bring-up experience: BIOS/UEFI configuration, firmware updates, component replacement, and OS installation across Linux distributions.

  • Linux command-line proficiency: enough to run diagnostics, inspect logs, and execute runbooks independently.

  • Asset management discipline: experience with DCIM or inventory tools and a track record of accurate, up-to-date records.

  • Strong written communication: you document what you do, escalate with context, and write SOPs others can follow.

  • Comfortable operating independently in a fast-moving startup environment.

 
Preferred Qualifications
  • Prior colocation data center experience (Equinix, CoreSite, Digital Realty, or similar).

  • Experience with AI/ML or GPU hardware: NVIDIA, AMD, or Intel accelerator cards in a lab or production environment.

  • Basic Ansible exposure — able to run playbooks and understand what they do.

  • Familiarity with high-speed interconnects: InfiniBand, RoCE, SFP/QSFP optics.

  • Python or Bash scripting for operational task automation.

 
Why This Role

You will be a critical part of the infrastructure that powers d-Matrix’s AI hardware development programs. In a small, high-ownership team, your work is immediately visible; when you bring up a system cleanly, the engineers depending on it notice. If you take pride in physical infrastructure done right and want to work at the cutting edge of AI silicon development, this is the role for you.

Equal Opportunity Employment Policy

d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day.

d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.

Skills Required

  • 3+ years in data center operations, hardware validation, or systems technician roles
  • Rack-and-stack experience including server installation, PDU and patch panel cabling, rack power planning, and professional cable management
  • Hardware bring-up experience: BIOS/UEFI configuration, firmware updates, component replacement, and OS installation across Linux distributions
  • Linux command-line proficiency to run diagnostics, inspect logs, and execute runbooks
  • Experience with DCIM or inventory tools and accurate asset tracking discipline
  • Strong written communication and documentation skills (SOPs, runbooks, escalation notes)
  • Comfortable operating independently in a fast-moving startup environment
  • Prior colocation data center experience (Equinix, CoreSite, Digital Realty, or similar)
  • Experience with AI/ML or GPU hardware (NVIDIA, AMD, or Intel accelerator cards)
  • Basic Ansible exposure (able to run playbooks and understand them)
  • Familiarity with high-speed interconnects: InfiniBand, RoCE, SFP/QSFP optics
  • Python or Bash scripting for operational task automation
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The Company
HQ: Santa Clara, CA
102 Employees

What We Do

d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.

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