Drive innovation in hardware efficiency by applying expertise in hardware reliability and performance, and translating insights into actionable strategies for hardware reliability and data center optimization Contribute to industry leading research in hardware characterization and fleet/DC efficiency studies across AI platforms, leveraging data-driven and machine learning analytical techniques Conduct in-depth hardware parameter based research and comparative analyses using advanced data analytics and machine learning techniques for failure analysis and diagnosis in production Interface with internal hardware, software engineers and operations teams to understand system architectures and failure modes Proactively create experiments, data analysis and data visualizations to detect and diagnose hardware health issues, focusing on systemic solutions Collaborate on evolving AI platforms, silicon products, thermal and cooling solutions to support the growth of large language models, with a focus on optimizing performance, scalability, and efficiency Develop data frameworks and discover insights to answer relationship between hardware, data center parameters and server failures Develop and implement data-driven strategies using hardware characterization studies to support hardware fleet optimizations and efficiency while supporting improvements to future platform designs Build comprehensive monitoring and predictive frameworks and to make data insights available to partner teams for decision making Collaborate with cross-functional teams to ingest and present data on evolving domains and specialized hardware technologies, components, datacenters Share insights with stakeholders and software teams to develop architectures to handle server failures based on hardware health data Troubleshoot, diagnose and root cause of system failures and isolate the components or failure scenarios with in depth statistical studies while working with stakeholders internally and externallyBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of hands-on software/firmware/hardware engineering to build systems/products for the IT industry Troubleshooting and data tooling, including data analysis, building analytical models, and visualizations Knowledge of server architecture and components across Compute/Storage/AI Systems/Networking Experienced in the integration of lab tools for automated workflows Experience with Linux systems and server systems management Master's degree or PhD in Computer Engineering, Electrical Engineering, or related field Proficient in SQL, Python or C/C++ (data structures, algorithms, and OOP) Experience with some of the following modules/domains: PCIe, Networking, Flash, Memory, CPU, GPU, DRAM (DDR4/5 or HBM)Meta builds technologies that help people connect, find communities, and grow businesses. HDRTP Engineers work closely with Production Engineering teams, Networking, Hardware Designers, Networking Teams, Manufacturers, Vendors, Datacenter Operation, Capacity, Core Systems and New Product Introduction teams to ensure the smooth operation of systems globally.