Hardware Systems Engineer, AI & HPC NPI

Meta; Menlo Park (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Meta in Menlo Park is seeking a Hardware Systems Engineer to support the NPI of AI and high-performance computing infrastructure for large-scale data centers. You will integrate AI silicon, server systems, and data center operations, collaborating with design, firmware, software, networking, and capacity teams to validate and scale AI hardware from early bring-up through production readiness.

Responsibilities include driving validation strategies for AI accelerators, GPUs, and memory subsystems;

Responsibilities

• Drive system validation strategies for AI and HPC hardware platforms, including AI accelerators, GPU clusters, and high-bandwidth memory subsystems in data center environments.
• Perform hands-on bring-up, characterization, and validation of AI server systems and associated components such as PCIe, NVLink, DRAM, and high-speed networking fabrics.
• Develop and maintain test specifications, validation procedures, and debug guides tailored to AI infrastructure NPI programs.
• Investigate and root-cause complex system failures spanning silicon, firmware, software, and hardware layers in collaboration with cross-functional engineering teams.
• Triage and track hardware and firmware defects through resolution while maintaining forward progress on NPI program milestones.
• Identify gaps in test coverage and contribute improvements to test methodologies, tooling, and automation frameworks across the NPI lifecycle.
• Partner with AI platform and capacity engineering teams to define acceptance criteria and deployment readiness standards for new AI hardware systems.
• Support data collection, analysis, and reporting efforts to surface systemic hardware quality trends.

Job description

Meta in Menlo Park is seeking a Hardware Systems Engineer to support the NPI of AI and high-performance computing infrastructure for large-scale data centers. You will integrate AI silicon, server systems, and data center operations, collaborating with design, firmware, software, networking, and capacity teams to validate and scale AI hardware from early bring-up through production readiness.

Responsibilities include driving validation strategies for AI accelerators, GPUs, and memory subsystems;