Software Engineer - High Performance Computing (Linux C++)

Job Description Summary We are looking for an experienced software engineer to develop and optimize high-performance, distributed computing solutions that support advanced semiconductor inspection and analysis systems. This role involves hands-on Linux C++ development, building scalable HPC frameworks, and improving performance across multi-node, CPU/GPU-accelerated environments. You will collaborate with cross-functional teams to design robust compute workflows, containerized deployments, and efficient data-processing pipelines that enable next-generation semiconductor manufacturing technologies. Role Overview This role focuses on designing, developing, and optimizing distributed, high-throughput software systems operating on advanced HPC infrastructure. The position requires strong technical ownership, hands-on Linux C++ development skills, deep performance engineering experience, and collaboration across multidisciplinary teams. Key Responsibilities Design and develop high-performance distributed software systems for large-scale HPC environments. Build and optimize Linux C/C++ components for compute-intensive and timing-critical workloads. Implement parallel/distributed computing frameworks using MPI, OpenMP, UCX, or similar technologies. Containerize and orchestrate compute workloads using Docker/Singularity with Kubernetes or SLURM. Profile, debug, and tune system performance using VTune, Nsight, perf, gdb, and related tools. Drive architectural discussions, code quality, and engineering best practices. Collaborate with algorithms, hardware, and systems teams to deliver tightly integrated solutions. Mentor team members in HPC concepts, system debugging, and performance optimization. Required Qualifications Strong hands-on expertise in C/C++ development on Linux, including systems-level programming. Proven experience building or optimizing HPC or distributed computing systems. Solid understanding of concurrency, multi-threading, networking, IPC, and Linux OS internals. Experience with profiling/debugging tools such as VTune, Nsight, perf, ftrace, gdb. Experience with Docker/Singularity and orchestration frameworks (Kubernetes, SLURM). Knowledge of CPU/GPU architectures, high-bandwidth interconnects, and distributed storage systems. Preferred Qualifications Experience using or optimizing MPI, OpenMP, UCX, SHMEM, or similar parallel programming models. Exposure to GPU compute frameworks (CUDA/RoC) or GPU-aware communication libraries. Familiarity with deep learning or ML pipeline workflows. Proficiency in Python and Bash scripting. Background in distributed microservices, observability tools, or large-scale system deployments. Education & Experience Bachelor's or Master's degree. Typically 6+ years of hands-on experience in HPC, Linux systems programming, or distributed systems development. Skills: high performance computing (hpc),multi-threading,openmpi,c++,linux,cpu/gpu architecture,mpi,systems programming