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-performance computing, including parallel or GPU programming (MPI, OpenMP, CUDA, Kokkos, etc.) Familiarity with modern software development practices, including debugging, profiling, and version control
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-based systems). Familiarity with GPU-accelerated computing (e.g., CUDA, NVIDIA ecosystem). Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications
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one of the above fields Very good expertise in the programming languages Python and C/C++, the numba library, and in applying parallelization techniques using GPU programming (CUDA/OpenCL) and MPI
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, CompTIA Network+/Security+; Experience with GPU environments (NVIDIA preferred), CUDA drivers, and related tools; Experience in research labs, AV systems, and hybrid on-prem/cloud setups. Job Duties and
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and train CNN and SNN models utilizing frameworks such as Keras, PyTorch, and SNNtorch Implement GPU acceleration through CUDA to enable efficient neural network training Apply hardware-aware design
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CUDA. What we can offer you: An opportunity to play a key role in a multidisciplinary team driving innovation in the deployment of deep neural network (DNN) models across a continuum of edge-to-cloud
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in 4D radar, thermal camera, SLAM or robotics software. Strong C++ and CUDA programming, with ROS1/2 experience. Experience in deploying SLAM on Jetson, ARM, or other edge platforms. Familiar with SLAM
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and domains. Ability to troubleshoot connectivity issues and familiarity with vulnerability management and patching processes. Python and nVidia CUDA modules setup and configuration. Relational database
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, successful experience with parallel programming using languages such as OpenCL and/or CUDA 7. Demonstrated, successful experience with source code version control systems such as Git, Subversion, or similar 8
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) environments 6. Demonstrated, successful experience with parallel programming using languages such as OpenCL and/or CUDA 7. Demonstrated, successful experience with source code version control systems such as