Lead AI Hardware Validation Engineer

Meta; Bellevue (WA); On-site; USD 144,000 - 204,000; Full time

Job summary

Meta is seeking a Hardware Systems Engineer to support the NPI of next-generation AI and HPC infrastructure for large-scale data centers.

You will work at the intersection of server systems, AI applications and data center operations, partnering with hardware design, firmware, software, networking, and capacity engineering teams to validate and scale cutting-edge AI hardware systems from early bring-up through production readiness.

Qualifications

• Bachelor's degree in CS/CE or equivalent.
• 6+ years in hardware systems engineering or AI server bring-up.
• Experience with ASIC bring-up, board-level debug, or large-scale data center validation.
• Experience developing test specifications, validation procedures, and debug methodologies.
• Experience leading root-cause analysis across hardware, firmware & software.
• Experience with PCIe, NVLink, DDR5, or HBM in AI/HPC validation.
• Experience analyzing telemetry and fleet health data.

Responsibilities

• Lead end-to-end validation strategies for AI and HPC hardware in data centers.
• Bring-up and validate AI server systems and components like PCIe, NVLink, memory.
• Develop test specs, validation procedures, and debug guides.
• Investigate root causes across silicon, firmware, software, and hardware.
• Track defects and progress milestones during NPI.
• Define acceptance criteria and deployment readiness with teams.

Skills

Python scripting

Linux server environments

Telemetry data analysis

Education

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Job description

Meta is seeking a Hardware Systems Engineer to support the NPI of next-generation AI and HPC infrastructure for large-scale data centers.

You will work at the intersection of server systems, AI applications and data center operations, partnering with hardware design, firmware, software, networking, and capacity engineering teams to validate and scale cutting-edge AI hardware systems from early bring-up through production readiness.