Develops, validates, debugs, and sustains GPU- and CPU-based high-performance computing hardware from prototype bring-up through large-scale production. The role requires 8–10+ years of experience, expertise in PCIe, InfiniBand, and NVMe, and proficiency in hardware-test automation.
215k – 260k/yr
On-site8+ YOEHardware Engineering
About the role
Responsibilities
Drive the full hardware development and sustaining lifecycle, including feasibility, bring-up, validation, deployment, and ongoing production support.
Develop and maintain scripting and automation frameworks for hardware testing, diagnostics, and continuous reliability improvements.
Lead deep troubleshooting and debugging across PCIe, InfiniBand, and NVMe/storage.
Conduct rigorous system validation and characterization for GPU, CPU, and high-performance compute platforms.
Support end-to-end integration and solution testing to ensure cloud products meet performance, reliability, and scalability expectations.
Collaborate with mechanical, thermal, firmware, software, and manufacturing teams to resolve system-level issues and enable stable production operation.
Drive prototyping, qualification, and readiness for high-volume manufacturing with internal teams and external vendors.
Identify opportunities for new hardware technologies, testing methods, and sustainability improvements.
Provide data-driven insights to influence the hardware roadmap and reliability strategy.
Requirements
8–10+ years of experience in hardware development, validation, sustaining engineering, or production engineering.
Strong hands-on expertise in PCIe, InfiniBand, and NVMe/storage debugging and development.
Deep proficiency in hardware bring-up, board-level debugging, and system-level validation.
Ability to design and implement automation frameworks for hardware testing using Python, Shell, or similar tools.
Technical background in digital and analog design, server architecture, and high-performance computing hardware.
Experience working across thermal, mechanical, firmware, and software functions in multidisciplinary environments.
Strong analytical and problem-solving skills with a data-driven approach.
Excellent communication and collaboration skills for working with internal teams and external partners.
Bachelor’s or master’s degree in Electrical Engineering, Computer Engineering, or equivalent experience.
Nice-to-Haves
Experience designing or optimizing GPU-to-GPU communication architectures for AI/ML workloads.
Direct experience integrating NVLink or other next-generation GPU interconnect technologies.
Familiarity with cutting-edge GPU architectures and their use in AI/HPC environments.
Experience supporting or designing systems across ARM and x86 server architectures.
Background in sustainable or energy-efficient hardware design practices.
Advanced certifications or coursework in AI/HPC hardware systems.
Compensation
Compensation range: $215,000–$260,000 annually.
Restricted Stock Units are included in all offers.
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