Principal HPC Architect

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. Group/Division 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. Job Description/Preferred Qualifications The Principal HPC Architect 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. Key Responsibilities: HPC Architecture & Engineering Design and implement HPC clusters, including compute, storage, networking, and job‑scheduling components. Evaluate and integrate new technologies (GPUs, accelerators, interconnects, filesystems). Develop automation for cluster provisioning, configuration, and lifecycle management. Architect solutions for large‑scale parallel workloads, AI/ML pipelines, and data‑intensive applications. Performance Optimization : 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. Operations & Reliability: Maintain and monitor HPC clusters, job schedulers (Slurm, PBS, LSF), and distributed filesystems (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. Automation & DevOps: 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.). Collaboration & Leadership: 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. Required Qualifications: 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 (InfiniBand, RoCE) and distributed storage systems. Proficiency in scripting languages (Python, Go, Bash) and automation frameworks. Experience with GPUs (NVIDIA CUDA, MIG, NVLink) and accelerator‑based computing. Familiarity with containerization (Singularity/Apptainer, Docker) in HPC contexts. Strong troubleshooting skills across hardware, OS, and application layers. Understanding of networking fundamentals (TCP/IP, DNS, load balancing) Background in high-availability and distributed systems at scale Soft Skills: Excellent communication and cross‑functional collaboration. Ability to translate research needs into technical solutions. Strong ownership mindset and ability to lead complex initiatives. Minimum Qualifications Doctorate (Academic) Degree and related work experience of 8 years; Master's Level Degree and related work experience of 12 years; Bachelor's Level Degree and related work experience of 15 years Base Pay Range: $162,700.00 - $284,700.00 Annually Primary Location: USA-CA-Milpitas-KLA KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave. Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including s