HPC Engineer

Company Overview

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice‑controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays.

The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem‑solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems.

There is never a dull moment with us.

The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.

The Staff HPC Engineer designs, builds, optimizes, and supports large‑scale compute environments used for scientific computing, AI/ML workloads, simulation, and data‑intensive research. This role blends systems engineering, performance tuning, cluster architecture, and hands‑on troubleshooting. The engineer partners with researchers, developers, and IT teams to deliver reliable, scalable, and high‑performance compute infrastructure.

• HPC Architecture & Engineering
• Design and implement HPC clusters, including compute, storage, networking, and job‑scheduling components.
• Evaluate and integrate new technologies (GPUs, accelerators, interconnects, file systems).
• Develop automation for cluster provisioning, configuration, and lifecycle management.
• Architect solutions for large‑scale parallel workloads, AI/ML pipelines, and data‑intensive applications.

• Profile and tune applications for CPU, GPU, memory, and I/O performance.
• Optimize MPI, OpenMP, CUDA, and other parallel programming frameworks.
• Benchmark hardware and software stacks to guide procurement and architecture decisions.

• Maintain and monitor HPC clusters, job schedulers (Slurm, PBS, LSF), and distributed file systems (Lustre, GPFS, BeeGFS).
• Troubleshoot complex system issues across compute, storage, and network layers.
• Implement security best practices, patching, and compliance controls.
• Ensure high availability and efficient resource utilization.

• Build and maintain CI/CD pipelines for HPC‑related software and infrastructure.
• Use tools such as Ansible, Terraform, Kubernetes, or custom scripts to automate workflows.
• Develop monitoring and observability solutions (Prometheus, Grafana, ELK, etc.).

• Work closely with researchers, data scientists, and engineering teams to support workload optimization.
• Provide technical leadership, mentorship, and guidance to junior engineers.
• Document architectures, procedures, and best practices.
• Participate in capacity planning and long‑term HPC strategy.

• Extensive experience with Linux systems engineering in large‑scale compute environments.
• Solid understanding of distributed systems and cloud infrastructure.
• Deep knowledge of HPC schedulers (Slurm preferred), MPI stacks, and parallel computing models.
• Strong understanding of high‑speed interconnects (Infini Band, RoCE) and distributed storage systems.
• Proficiency in scripting languages (Python, Go, Bash) and automation frameworks.
• Experience with GPUs (NVIDIA CUDA, MIG, NVLink) and…