Pong Eksombatchai is a Research Engineer with 14 years of experience building and scaling production ML systems, now at Google DeepMind after leading ML infrastructure and recommender system efforts at Pinterest. At Pinterest he drove a 2000x scale-up of critical recommendation models through full-stack optimization and model-infrastructure co-design, effectively owning recommender advancements for four years. He blends research rigor from Stanford with hands-on engineering across serving, training, and feature pipelines, and has a strong track record in ads and search systems from earlier roles. Based in Los Gatos, he couples deep systems expertise with product-minded execution, known for squeezing orders-of-magnitude efficiency gains that enable new product capabilities.
13 years of coding experience
13 years of employment as a software developer
Master's Degree Financial Mathematics, Master's Degree Financial Mathematics at Stanford University
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
Contributions:2 pushes, 1 branch in 8 days
pytorchsparse-matrixsparseoptimizedmatrix
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Pong Eksombatchai - Research Engineer at Google DeepMind