
Production Systems Engineer, AI Systems
Required skills
- AI accelerators
- GPU clusters
- TPUs
- ASIC bring-up
- board-level debug
- firmware validation
- large-scale system validation
- PCIe
- NVLink
- DDR5
Nice to have
- InfiniBand
- Python
- scripting
- AI training process
- Linux
- data center management tooling
Role summary
Meta is looking for a Hardware Systems Engineer to support the introduction of next-generation AI and high-performance computing infrastructure in data centers. This role involves working at the intersection of server systems, AI applications, and data center operations. You will partner with cross-functional teams to validate and scale cutting-edge AI hardware systems from early bring-up through production readiness. Responsibilities include leading system validation strategies, driving hands-on bring-up and characterization, developing test specifications, and root-causing complex system failures. The role also involves identifying test coverage gaps, defining acceptance criteria, guiding data analysis, and communicating findings to stakeholders.
Responsibilities
- Lead end-to-end system validation strategies for AI and HPC hardware platforms, including AI accelerators, GPU clusters, and high-bandwidth memory subsystems in data center environments
- Drive 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 their resolution while maintaining forward progress on NPI program milestones
- Identify gaps in test coverage and drive 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
- Guide data collection, analysis, and reporting efforts to surface systemic hardware quality trends and inform go/no-go decisions for production deployment
- Communicate validation status, risk assessments, and technical findings to internal engineering teams and external hardware vendors
- Collaborate with firmware and software teams to define hardware-software interface requirements for telemetry, diagnostics, and remote management of AI infrastructure
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 8+ years of experience in hardware systems engineering, silicon validation, firmware validation, or system-level bring-up for AI servers, GPUs, TPUs, or AI accelerator platforms
- Experience in one or more of the following domains: ASIC bring-up and characterization, board-level debug, firmware validation, or large-scale system validation in data center environments
- Experience in developing test specifications, validation procedures, and debug methodologies for complex hardware systems
- Experience with high-speed interconnects or memory subsystems such as PCIe, NVLink, DDR5, or HBM in the context of AI or HPC system validation
- Experience leading root-cause analysis and troubleshooting of system-level failures across hardware, firmware, and software stacks
- Experience analyzing system telemetry and fleet health data to identify reliability trends and drive engineering improvements
- Experience leading projects with large teams
Preferred Qualifications
- Experience with high-speed interconnects and memory subsystems such as PCIe, NVLink, InfiniBand, DDR5, or HBM in the context of AI or HPC infrastructure operations
- Proficiency in scripting or programming languages such as Python for the automation of infrastructure workflows and data analysis
- Understanding of the AI training process
- Familiarity with Linux-based server environments and data center management tooling used in large-scale production operations
- Experience defining hardware-software interface requirements for telemetry, out-of-band management, or remote diagnostics in data center AI systems
$173,000/year to $245,000/year + bonus + equity + benefits
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