Shikib Mehri

Applied Scientist at Amazon

San Jose, California, United States
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Summary

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Senior
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Top School
Shikib Mehri is an applied scientist based in San Jose with 11 years of experience translating cutting-edge NLP research into production products, currently leading reward modeling, evaluation, and data collection efforts for LLM features at Amazon. A Carnegie Mellon PhD student focused on dialog systems, he has a strong track record across industry research internships and roles at Facebook, Microsoft, and Amazon, and academic work on conversational thread disentanglement and graph-based read alignment. He independently built initial reward model pipelines and evaluation methodologies that shaped program-level practices, and has run end-to-end annotation efforts aligning data collection with product requirements. Comfortable moving between research and engineering, he combines peer-reviewed publications with measurable product impact (e.g., shipped MT improvements and conversational ASR work), reflecting a pragmatic researcher who ships.
code11 years of coding experience
job4 years of employment as a software developer
bookThe University Transition Program
bookBachelor of Science (BSc), Honours Computer Science, Senior Year, Bachelor of Science (BSc), Honours Computer Science, Senior Year at The University of British Columbia
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
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Stackoverflow

Stats
1reputation
324reached
0answers
1question
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Github Skills (89)

messaging10
messenger10
class-diagram10
telegram10
chat10
code-generation10
state-machine10
tdlib10
telegram-client10
telegraph10
uml10
mtproto10
modeling10
dialog9
datasets9

Programming languages (5)

JavaC++CJavaScriptPython

Github contributions (5)

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Contributions:5 commits, 5 pushes, 1 branch in 5 months
Code for the SIGDial 2021 paper: Schema-Guided Paradigm for Zero-Shot Dialog
Contributions:4 commits, 2 PRs, 2 pushes in 2 months
dialogzerozero-shotparadigmsigdial
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