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David Peleg has a diverse work experience. David started their career as a QA Automation Engineer at IBM, where they automated stress tests for the company's cloud infrastructure. David then worked as a Teaching Assistant at Bar-Ilan University before joining Intel Corporation as a Data Science Intern. At Intel, they developed a solution to split Deep Neural Networks using PyTorch and Fairscale and optimized DNN workloads using sampling methods. David also gained experience with parallelization frameworks like PyTorch Lightning and DeepSpeed. Later, at Intel Corporation, they worked as a Data Science Researcher, where they created a graph compiler to execute DNNs on a proprietary hardware simulator and used reinforcement learning and evolutionary methods to optimize DNN workloads. In their most recent role, David is a Deep Learning Engineer at AUIâ„¢ (Augmented Intelligence) since 2023.

David Peleg completed their Bachelor of Science (BS) in Computer Science and Physics at Bar-Ilan University from 2016 to 2019. Following the completion of their bachelor's degree, they pursued a Master of Science (MS) in Theoretical and Mathematical Physics at the same university from 2019 to 2021.