Hardware Reliability Engineer - Memphis
xAI · Southaven, Mississippi; Memphis, Tennessee
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SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
ABOUT THE TEAM:
The Hardware Reliability team is committed to the reliability of datacenter compute hardware. As part of this team, you use data to understand the factors that drive reliability, and use these to drive improvements in design, manufacturing, test, and deployment. You have the ability to dive deep on the details to identify, understand and solve difficult technical problems and also utilize a system level approach to prioritize issues for the compute nodes as a whole. You thrive in a hands-on environment and will spend time in the office, on the datacenter floor, and in the lab to strive for 100% GPU uptime. You will determine the true root cause of compute node hardware failures — component and system level — and drive fixes through vendors to the manufacturer.
RESPONSIBILITIES:
- Responsible for tracking yield, test/inspection escapes, and ensuring past failures and lessons learned are incorporated
- Monitor the success of products and processes through production ramp-up using a suite of quality and analysis tools
- Conduct regular build quality reviews to ensure that design intent is achieved and well-communicated; identify opportunities for risk reduction and removal of complexity in designs and processes to improve manufacturability, collaborating with integrated product teams to drive improvements and address high-impact and repeating non-conformances
- Investigate failures in test and deployment, identifying and mitigating the immediate and underlying root causes in order to quantify/reduce risk and improve reliability of designs and processes
- Utilize schematics, test equipment, inspection processes, etc. to perform structured electrical root cause analysis of failures identified during the development and production processes to inform design/manufacturing changes
- Identify failures across GPU trays/baseboards, NIC/DPU, motherboard/PCIe switch, memory, power, thermal, cables/connectors, and rack-scale patterns
- Failure identification includes down to the piece part and circuit board level
- Diagnose and prove complex hardware failures, including intermittent issues, using failure analysis tools, logic analyzers, or diagnostic software
- Run recurrence analysis and datacenter-wide defect clustering; detect systemic and component level patterns before they become fleet-scale loss.
- Build vendor technical escalation packages with evidence quality that forces action; partner with OEM/ODM/component manufacturers on firmware, bring-up, and manufacturing escapes through committed CAPA.
QUALIFICATIONS:
- Bachelor's degree in electrical engineering, computer engineering, mechanical engineering, or equivalent
- Hands on experience designing and/or troubleshooting PCBAs
- Proficiency in scripting (Python, Bash, Perl) for automation and analysis
PREFERRED SKILLS AND EXPERIENCE:
- Experience supporting production and test of complex electromechanical assemblies
- Experience in at least one system language (C, C++, Java, Rust, or similar).
- Experience with RMA processes, including filing claims, vendor negotiations, and pushing for resolutions outside standard protocols.
- Knowledge of quality tools such as Lean principles, measurement systems analysis, design of experiments, statistical process control,, root cause analysis and corrective action, advanced product quality planning (APQP), metrology, process failure mode and effects analysis (PFMEA), control plans, and various problem solving approaches
- Dedicated to adopting a Lean approach to quality without compromising safety or reliability
- Knowledge of hyperscale compute vendor ecosystems (e.g., NVIDIA, Dell, HP, Supermicro) and supply chain management
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
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