Cole Howard is a Machine Learning Engineer in Portland, OR with 11 years of applied experience building and shipping deep learning and NLP systems from research to production. He has led engineering and data science teams and shipped practical models—Siamese CNNs for document similarity, LSTM/CNN ensembles for candidate/job attribute prediction, and production recommendation engines—across startups and e-commerce. Cole co-authored chapters in Manning's "Natural Language Processing in Action," demonstrating both pedagogical clarity and hands-on expertise in neural architectures. He pairs Bayesian optimization and transfer learning with interpretability tools like LIME to reduce bias and tune large models for real-world use. Comfortable moving between prototype research and scalable deployment, he brings a mathematician’s rigor to solving messy product problems.
11 years of coding experience
17 years of employment as a software developer
Bachelor of Arts (B.A.), Mathematics, Bachelor of Arts (B.A.), Mathematics at University of Michigan
Contributions:45 commits, 28 pushes, 3 branches in 8 months
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