High Performance Compute (HPC) Software Engineer – HPC SW Systems

KLA•Ann Arbor, MI

1d•Onsite

About The Position

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.

Requirements

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
Strong experience developing HPC or systems software on Linux.
Proficiency in Java and/or C++ and/or other system-level or performance-oriented languages.
Hands-on experience with parallel computing (MPI, OpenMP, multithreading).
Solid understanding of HPC hardware fundamentals: CPUs, memory hierarchies, storage, networking (Ethernet / InfiniBand).
Practical experience working with clusters, servers, or rack-scale systems in lab or production environments.
Strong debugging skills across software, OS, and hardware boundaries.

Nice To Haves

Candidates with GPU computing (CUDA, ROCm, or equivalent) would be preferred.
Experience with containerized HPC environments (Docker, Singularity/Apptainer, Kubernetes in HPC contexts).
Familiarity with high-speed interconnects, storage architectures, and performance benchmarking.
Exposure to rack integration, including cabling, power distribution, cooling, and system bring-up.
Experience in semiconductor, manufacturing, or high-reliability systems environments.
Ability to reason about system reliability, MTBF/MTBA, and failure modes in large compute installations.

Responsibilities

Design, develop, and optimize HPC software running on large-scale Linux clusters, including distributed and parallel workloads (MPI, multithreading, GPU-accelerated pipelines, containerized workloads).
Optimize application performance and power utilization across CPU, memory, storage, and network subsystem, with attention to throughput, latency, and scaling behavior.
Develop and maintain system-level tooling for cluster bring-up, diagnostics, monitoring including component power usages, and health checks.
Work closely with algorithms, systems and application teams to understand and translate workload characteristics into power-efficient HPC software solutions.
Collaborate with hardware and systems teams to define HPC node, storage, and interconnect requirements based on software and algorithm needs.
Understand and influence CPU/GPU selection, memory sizing, PCIe layout, NUMA behavior, and network topology to ensure optimal software performance.
Participate in HW/SW co-debug activities, including performance bottlenecks, stability issues, and failure analysis.
Understand rack-level integration of HPC systems, focusing on power, cooling, cabling, networking, and physical layout considerations.
Understand data-center and lab constraints such as power budgets, thermal limits, network drops, and serviceability.
Contribute to best practices, and design reviews for new platforms and refresh cycles.
Act as a technical bridge between software, hardware, systems teams.
Provide clear technical documentation covering software and system architecture, deployment flows, performance assumptions.