AI Workload Performance Storage Engineer
4 weeks ago
Transforming the Future of Data Storage
Micron Technology is a world leader in developing innovative storage solutions that accelerate the transformation of information into intelligence. We are seeking a highly skilled Storage Performance Engineer for AI Applications to join our Data Center Workload Engineering team.
The emergence of Artificial Intelligence is driving changes in storage system architectures within data centers. Our team is looking for an engineer to characterize flash-based media for AI applications and storage systems. If you have hands-on problem-solving skills and an aptitude for learning new technologies, we want to discuss this opportunity with you.
Key Responsibilities:
- Design, develop, and deploy AI solutions that simulate customer environments.
- Collect and analyze storage traces of AI workloads, uncovering and classifying unique IO behavior.
- Devise and implement suitable benchmarking strategies, drawing from industry standards and field feedback.
- Automate and expand existing benchmarking capabilities to improve efficiency and repeatability.
- Demonstrate skills at instrumenting and measuring application workload requests, analyzing storage solution I/O activity down to SSD devices, and monitoring system resource utilization.
- Analyze system-level bottlenecks and solve issues involving virtualization technologies, distributed storage architectures, and complex application workload environments.
- Interpret findings and results, summarizing into standard methodologies, white papers, and presentations to help SSD engineering understand unique AI workload requirements.
- Work with multi-functional teams and key partners to deliver prescriptive guidance documents to position our storage products in premier application environments.
- Drive continuous improvement feedback to Micron product development organizations.
- Improve efficiency by automating solution deployment, benchmark tests, and related procedures.
Requirements:
- Understanding of emerging AI workloads and their impact and requirements on system architecture.
- Expert understanding of Python.
- Experience with hypervisors and SDS stacks: VMware ESX, VSAN, Microsoft Hyper-V, Azure Stack HCI, Ceph, Docker, Linux Containers.
- Synthetic I/O characterization and related tools – IOMeter, vdbench, FIO, Blktrace, etc.
- Operating systems and associated internal storage stacks: Microsoft, VMware, Linux.
- IP network design and deployment: VLAN, RoCE, Infiniband.
- Familiarity with and knowledge of Solid State Drives and related technologies.
- Experience in Data Center SSD validation is a plus.
- Excellent oral and written communication skills.
Education:
A bachelor's or master's degree and 5+ years of relevant engineering experience.
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