Micron's Data Center Workload Engineering team tests how memory and storage products perform in complete data center systems. We deploy customer-representative AI, database, virtualization, and software-defined storage workloads in production-class labs. We trace I/O from the application through the system to the SSD to explain performance and identify opportunities to improve it. As a Principal Systems Performance Engineer, you will lead complex performance studies from the initial question through the final recommendation. You will personally lead the hardest investigations while setting technical direction for the team. Your work will guide SSD architecture and product development and help customers get the best performance from Micron products. This is a hands-on senior individual-contributor role. Key Responsibilities • Lead application performance studies on enterprise servers, GPU-accelerated systems, and data center storage platforms. • Deploy customer-representative workloads across one or more areas, such as AI training and inference, checkpointing, KV-cache offload, data preparation, databases, virtualization, and software-defined and object storage. • Develop test plans with clear hypotheses, realistic configurations, appropriate controls, and repeatable methods. • Instrument systems and trace I/O from the application through the software and storage stack to the SSD. Measure application throughput, completion time, scaling efficiency, tail latency, consistency, and power, then correlate those results with system and device telemetry. • Isolate bottlenecks across applications, operating systems, drivers, networks, PCIe, NVMe, and storage devices. Recommend software, system, or product changes based on the findings. • Build automation, test harnesses, and analysis tools that improve test coverage, repeatability, and turnaround time. • Evaluate new SSD features, system architectures, and competing solutions with real applications and customer use cases. • Turn test results into engineering reports, technical briefs, reference architectures, and presentations for engineering teams, customers, and executives. • Work directly with SSD architects, product engineers, customer teams, and ecosystem partners to translate findings into architecture, product-roadmap, software, and customer-deployment decisions. • Set technical direction for performance work, review methods and results, and mentor engineers across the team. Required Qualifications • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, with 8 years of experience. • Extensive experience leading complex systems performance, application benchmarking, or workload characterization work. • Hands-on experience deploying and debugging data center applications on Linux systems. • Deep understanding of system performance and the storage I/O path, including Linux I/O, file systems, block storage, NVMe, and PCIe. • Experience with performance and system-analysis tools such as perf, eBPF, bpftrace, application profilers, fio, or equivalent tools. • Proficiency in Python or another language used to automate tests and analyze data. • Demonstrated ability to lead ambiguous technical work, identify root causes, and make recommendations supported by data. • Clear written and verbal communication with engineering, customer, and executive audiences. Preferred Qualifications • Experience testing AI infrastructure or another production data center workload domain such as databases, virtualization, high-performance computing, or distributed storage. • Experience with GPU-accelerated systems and AI frameworks. • Experience with software-defined or object storage platforms such as WEKA, Ceph, Cloudian, or MinIO. • Experience measuring power, efficiency, quality of service, or storage device behavior under application load. • A record of technical influence through product decisions, customer outcomes, design reviews, reusable tools, publications, patents, or open-source contributions.