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Parallel Computing Engineer at Mercor. Location Information: India. This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.. Role Description. This role involves accelerating numeric and simulation kernels through GPU/CPU parallelism, memory-hierarchy tuning, and distributed execution across clusters. You’ll design scalable pipelines that maximize efficiency and throughput for large-scale computational workloads.. 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. . Qualifications. 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. . Requirements. Design, optimize, and deploy parallel computing pipelines that accelerate numeric, simulations, and large-scale computations across GPUs, CPUs, and distributed clusters. . Benefits. Classified as an hourly contractor to Mercor. . Paid weekly via Stripe Connect, based on hours logged. . Part-time (20–30 hrs/week) with flexible hours—work from anywhere, on your schedule. . Weekly Bonus of $500–$1000 USD per 5 tasks. . Remote and flexible working style.