HPC Windows Server Infrastructure Engineer

KLA•Milpitas, CA

17h•$136,300 - $199,900•Onsite

About The Position

KLA's eBeam division develops industry-leading semiconductor inspection systems powered by advanced computing infrastructure, AI, and large-scale analytics. We are seeking a hands-on engineer to design, deploy, and optimize Windows-based environments that support next-generation high-performance computing (HPC) platforms. This role is ideal for an engineer with strong Windows Server expertise who enjoys solving complex infrastructure challenges across hardware, software, networking, and automation.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or related field.
3 to 5 years of experience deploying and administering Microsoft Windows Server (2012-2025) environments.
Configuration Manager OSD (SCCM), Microsoft Deployment Toolkit (MDT), ADK, WinPE, and Windows Deployment Services (WDS)
Active Directory, Group Policy, DNS, and DHCP
PowerShell scripting and automation
Hyper-V and virtualization concepts
TCP/IP networking fundamentals and enterprise infrastructure services
Configuration management and deployment automation
x86 server hardware, system integration, and performance optimization
Storage technologies including RAID, HBA controllers, and JBOD architectures
Hardware bring-up, device drivers, and system diagnostics
Python for automation and infrastructure management

Nice To Haves

Microsoft certifications (MCSE or equivalent)
Experience supporting HPC, AI, or GPU-accelerated compute environments
Experience with Docker, Kubernetes, or containerized workloads
Configuration management and Infrastructure-as-Code tools
CI/CD tools such as Jenkins and Git
Monitoring platforms including Grafana and Prometheus
PKI, SSL/TLS certificates, and security best practices
Workload schedulers such as Slurm
Cloud platforms including Azure, AWS, or Google Cloud

Responsibilities

Configure, deploy, and optimize Microsoft Windows Server environments supporting HPC and AI workloads.
Develop and maintain system images, deployment processes, and infrastructure automation.
Support compute, storage, networking, and GPU-based platforms used in advanced semiconductor inspection systems.
Create and maintain deployment, monitoring, and diagnostic tools using PowerShell and Python.
Perform hardware integration, qualification, benchmarking, and performance optimization.
Collaborate with software, hardware, manufacturing, and field teams to support product development and deployment.
Drive infrastructure refresh and scalability initiatives supporting future product generations.