Contractor Parallel Computing Engineer

• Speed up numeric and simulation kernels through GPU/CPU parallelism.
• Optimize workloads via memory-hierarchy tuning and communication reduction.
• Scale computations with MPI, NCCL, and Slurm for distributed clusters.
• Profile and benchmark performance using nvprof and nsys.
• Build reproducible pipelines in Python, NumPy, and SciPy for HPC workflows.
• Collaborate with researchers and engineers to integrate HPC into production AI systems.

• Background in computer science, high-performance computing, or applied mathematics.
• Experienced with GPU/CPU parallel programming using CUDA and OpenMP.
• Understanding of distributed execution frameworks and tools like MPI, NCCL, and Slurm.
• Proficient in Python with libraries like NumPy and SciPy for scientific computing.
• Experience profiling and optimizing workloads with tools like nvprof and nsys.
• Care about memory hierarchy, communication overhead, and scalability in parallel systems.
• Curious about how HPC techniques accelerate AI training, simulations, and scientific workloads.

• Design, optimize, and deploy parallel computing pipelines that accelerate numeric, simulations, and large-scale computations across GPUs, CPUs, and distributed clusters.

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