Algorithm Software Architecture

To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale—faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology.

Group/Division The Semiconductor Products and Customers (Semi PC) business unit designs, builds and sells KLA’s product portfolio to help chip manufacturers meet high-quality standards for technologies like AI, data centers, automotive and electronic devices. Our inspection, metrology, and analytics systems detect and monitor defects across logic and memory chips, specialty semiconductors, wafers, reticles, advanced packaging, process equipment and materials. We also develop technologies for specialty processes, IC substrates, and PCB manufacturing, including etch and deposition, component inspection, and imaging and analytics.

The Film and Scatterometry Technology (FaST) division delivers industry-leading metrology solutions essential to advanced semiconductor manufacturing. Its portfolio includes systems for measuring film thickness, critical dimensions, composition, and resistivity—key to developing and scaling next-gen IC processes. FaST partners closely with customers from early R&D through high-volume production, ensuring performance and process alignment.

What You'll DoIn this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise.

Overview We are seeking a Senior Algorithm Software Architect to lead design and delivery of GPU‑accelerated, high‑performance computing software. You will set architectural direction, coach engineers, and partner with product and domain experts to deliver scalable, reliable systems for large‑scale compute and data workflows.

Responsibilities Own the end‑to‑end software architecture for HPC/GPU platforms (services, libraries, data pipelines, deployment)
Lead technical strategy, decision records, define candidate architectures, lead design reviews and drive decisions; drive clear trade‑offs for performance, reliability, and maintainability

Design and implement GPU kernels and frameworks (e.g., CUDA, OpenCL, NCCL), optimizing for throughput, latency, and memory use Guide parallel and distributed computing patterns (MPI, multi‑GPU scaling, heterogeneous compute)
Establish performance engineering practices: profiling, benchmarking, regression performance gates (Nsight Systems/Compute, nvprof)
Collaborate across functions; convert requirements into clear technical plans, roadmaps, and measurable outcomes

Uphold engineering excellence: coding standards, code reviews, test strategies, observability, security considerations

Mentor engineers; provide technical leadership on design, delivery, and career growth.

Communicate architecture, risks, and status to executives and stakeholders with clarity and candor.

Qualifications
10+ years in software engineering; 5+ years in software architecture for HPC or large‑scale systems

Expert in C++ (17/20) and one scripting language (Python preferred)
GPU programming expertise (CUDA, OpenCL); strong knowledge of GPU memory hierarchies, streams, occupancy

Hands‑on with parallel/distributed stacks (MPI, NCCL, gRPC) and Linux performance tooling

Experience with cluster orchestration (Slurm, Kubernetes), CI/CD, and containerization (Docker)
Track record of technical leadership and exceptional communication with cross‑functional teams.

Preferred / Nice‑to‑Have Multi‑node, multi‑GPU scaling; mixed precision; numerical methods and algorithms.

Experience with H200/H100/A100/L40S‑class accelerators and modern…