Senior Hardware Systems Engineer

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 link training, topology, and performance issues
  • InfiniBand fabric debugging, throughput, and connectivity issues
  • NVMe/storage performance bottlenecks, firmware interactions, and failure analysis
• 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.
• Expertise 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 and Benefits

• Compensation range: $170,000–$205,000.
• Restricted Stock Units are included in all offers.