Mohammad Shoeybi is a Senior Staff Research Manager at NVIDIA with eight years of experience leading applied deep learning teams to build large-scale language models and production NLP solutions. He has a strong track record of translating cutting-edge research into product impact, previously leading ML and RL efforts at DeepMind for YouTube and shipping speech and TTS systems at Baidu. Comfortable across low-level high-performance engineering (C++, CUDA, MPI, OpenMP) and ML stacks (TensorFlow, Spark, Docker), he routinely bridges algorithmic innovation with scalable production systems. His background in computational fluid dynamics (MS/PhD from Stanford) and early work on massively parallel scientific code reflect a long-standing focus on numerical optimization and performance at scale. Known for assembling and mentoring cross-functional teams, he often combines hands-on prototyping with delivery responsibilities. Based in California, he brings a rare mix of academic rigor and product-oriented engineering to large-scale AI deployments.
8 years of coding experience
9 years of employment as a software developer
MS, Mechanical Engineering, Computational Fluid Dynamics, MS, Mechanical Engineering, Computational Fluid Dynamics at Stanford University
BS, Mechanical Engineering, Non-linear Vibration Analysis and Control, BS, Mechanical Engineering, Non-linear Vibration Analysis and Control at Sharif University of Technology
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Mohammad Shoeybi - Senior Staff Research Manager at NVIDIA