Production Systems Engineer, Hardware Analytics

Responsibilities

• 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 externally

Minimum Qualifications

• Bachelor'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

Preferred Qualifications

• 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)

Compensation

• $173,000/year - $245,000/year; Country: US; Bonus eligible; Equity eligible

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