Meta is seeking a Hardware Systems Engineer to join our Release to Production (RTP) team working on new NPI hardware. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure operates efficiently to deliver our innovative services. The RTP team is responsible for the end-to-end Hardware Lifecycle of all Meta servers including prototyping of experimental HW, pre-production hands-on system and hardware debugging and stress testing, enabling production-ready system monitoring, automated provisioning and automated remediation of issues. RTP team also helps in exploring, developing and productizing high-performance software and hardware technologies for AI at datacenter scale. Hardware Systems Engineer in RTP work closely with HW/SW co-design teams, hardware designers, networking teams, system manufacturers, component vendors, capacity engineering, production engineering, production services, and data center operations teams to enable new systems that will be deployed in our production data centers. We also work across service and hardware architectures for new AI systems, build prototypes to demonstrate the value, enable go/no-go decisions and optimize these systems in production.

• Interface with external vendors and internal hardware, mechanical, power, thermal, manufacturing and software engineers to understand system architecture to guide and develop Hardware Fault Management for various server products.
• Leverage deep understanding RAS (reliability, availability, serviceability) to improve error reporting and error handling mechanism for better operation quality and cost/efficiency.
• Champion engineering and operational excellence, establishing metrics and process for regular assessment and improvement.
• Develop visibility through data visualization and implement systemic solutions to hardware health issues.
• Proactively create experiments and tooling to detect and diagnose hardware/firmware/software health issues.
• Troubleshoot, diagnose and root cause of system failures and isolate the components/failure scenarios while working with internal & external stakeholders.
• Drive necessary discussion with external and internal teams on test specification and methodologies to improve test quality continuously.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 5+ years of work experience in one or more domains such as: ASIC development (Silicon design or bringup or characterization), compute (ARM, x86), AI-ML hardware/software (GPUs, TPUs).
• Knowledge of architecture and components on one of the following products: server/PC/Laptop.
• Development or debug experience in one or more following areas: hardware fault management, error reporting, error handling on hardware products.

• 7+ years of experience with one subset of the following AI systems: Accelerator (GPU/ASIC), Kernel development, Performance optimization (e.g., NVIDIA, AMD, Intel, or other misc accelerator), computer architecture, HPC communication libraries (e.g., NCCL, MPI), performance enablement, tracing, profiling and debugging.
• Experience with architecture of disaggregated systems at scale.
• Understanding of hardware development process and how to scope out test plans accordingly.
• Experience troubleshooting problems at system level, crossing across multiple components, as well as hardware/firmware/software boundaries.