Senior HPC Software Engineer

As an experienced software engineer focusing on designing, developing, and optimizing distributed, high-throughput software systems operating on advanced HPC infrastructure, you will play a critical role in the following key responsibilities: - Designing and developing high-performance distributed software systems for large-scale HPC environments. - Building and optimizing Linux C/C++ components for compute-intensive and timing-critical workloads. - Implementing parallel/distributed computing frameworks using MPI, OpenMP, UCX, or similar technologies. - Containerizing and orchestrating compute workloads using Docker/Singularity with Kubernetes or SLURM. - Profiling, debugging, and tuning system performance using VTune, Nsight, perf, gdb, and related tools. - Driving architectural discussions, code quality, and engineering best practices. - Collaborating with algorithms, hardware, and systems teams to deliver tightly integrated solutions. - Mentoring team members in HPC concepts, system debugging, and performance optimization. To be successful in this role, you should possess the following 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. Additionally, the following preferred qualifications would be beneficial: - 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. Your educational background should include a Bachelors or Masters degree with typically 6+ years of hands-on experience in HPC, Linux systems programming, or distributed systems development. As an experienced software engineer focusing on designing, developing, and optimizing distributed, high-throughput software systems operating on advanced HPC infrastructure, you will play a critical role in the following key responsibilities: - Designing and developing high-performance distributed software systems for large-scale HPC environments. - Building and optimizing Linux C/C++ components for compute-intensive and timing-critical workloads. - Implementing parallel/distributed computing frameworks using MPI, OpenMP, UCX, or similar technologies. - Containerizing and orchestrating compute workloads using Docker/Singularity with Kubernetes or SLURM. - Profiling, debugging, and tuning system performance using VTune, Nsight, perf, gdb, and related tools. - Driving architectural discussions, code quality, and engineering best practices. - Collaborating with algorithms, hardware, and systems teams to deliver tightly integrated solutions. - Mentoring team members in HPC concepts, system debugging, and performance optimization. To be successful in this role, you should possess the following 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. Additionally, the following preferred qualifications would be beneficial: - 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. Your educational background should include a Bachelors or Masters degree with typically 6+ years of hands-on experience in HPC, Linux systems programming, or distributed systems development.