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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 18 days ago
GPUs using ROCm, HIP, and related translation tools. REQUIRED: Bachelor's degree or equivalent with a minimum of five years of work experience in either deeply technical fields and/or computational
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fields and/or computational research experience; strong proficiency in Python and C++, with deep familiarity with AI/ML frameworks (PyTorch, TensorFlow, JAX); hands-on experience with GPU programming
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well as large-scale GPU computing facilities for deep learning. We are looking for a Research Engineer to manage the EEE GPU Cluster. The role will focus on enhancing the EEE GPU Cluster team’s ability in terms
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Internal Number: 25597 INFORMATION SECURITY MANAGER, The Massachusetts Green High Performance Computing Center (MGHPCC ), to serve as the primary security leader across MGHPCC and the AI Computing Resource
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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modeling). Experience working with HPC/GPU resources and job schedulers (e.g., Slurm) and/or cloud-based deployments. Track record of contributing to peer-reviewed publications as a computational specialist
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FLAME-GPU accelerated agent-based modelling of material response to environmental and operational loading EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce
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Language Model (LLM) GPU cluster to ensure stable and reliable operation of training tasks; (b) handle GPU node failures, IB network anomalies, CUDA/NCCL errors and Kubernetes scheduling failures, perform
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to support efficient model training iteration; (b) lead the construction of the GPU computing cluster centered around a Kubernetes + NVIDIA GPU Operator, including node planning, resource management
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(URCF) at Drexel University is building a new shared computing platform focused on GPU-accelerated workloads, particularly AI model training. The system includes GPU and CPU compute nodes with Nvidia H200