Daniel Hewlett
Principal Staff Software Engineer, Machine Learning at LinkedIn
Sunnyvale, California, United States
Summary
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Senior🎓
Top SchoolDaniel Hewlett is a Principal Staff Software Engineer specializing in machine learning and AI, with nine years of industry experience and a Ph.D. in Computer Science from the University of Arizona. He leads ML efforts at LinkedIn, driving deep learning improvements for search, recommendations, and hiring workflows after progressing through senior engineering roles at LinkedIn and Google/YouTube. His research background in natural language understanding and robotics—dating back to a dissertation system for robots learning instructions and a record-setting unsupervised word segmentation algorithm—helps him bridge academic advances and production-grade systems. Known for turning complex language and recommendation problems into measurable product gains, he combines research rigor with large-scale engineering judgment. Based in Sunnyvale, he blends hands-on model development with mentoring and cross-functional influence, often surfacing subtle data and modeling signals that improve user-facing relevance. Beyond product impact, his career shows a consistent theme of connecting human communication and machine intelligence in practical deployments.
10 years of coding experience
19 years of employment as a software developer
The University of ArizonaM.S. Computer Science, M.S. Computer Science at University of Southern CaliforniaB.S. B.A. B.A. Computer Science Linguistics Philosophy, B.S. B.A. B.A. Computer Science Linguistics Philosophy at University of Maryland
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
language-understanding9
linkedin6
training-data4
machine-learning3
tensorflow2
deep-learning2
Programming languages (2)
Github contributions (3)
google-research-datasets/wiki-reading
Aug 2016 - Mar 2017
This repository contains the three WikiReading datasets as used and described in WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia, Hewlett, et al, ACL 2016 (the English WikiReading dataset) and Byte-level Machine Reading across Morphologically Varied Languages, Kenter et al, AAAI-18 (the Turkish and Russian datasets).
Contributions:3 commits, 1 PR, 1 push in 7 months
language-understanding
danielhewlett/wiki-reading
Aug 2016 - Aug 2016
Contributions:1 push, 2 branches in 1 day
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