Daniel Nkemelu
Applied Scientist II at Amazon
Bellevue, Washington, United States
Summary
👤
Senior🎓
Top SchoolDaniel Nkemelu is an applied scientist specializing in LLM training and inference optimization, currently advancing AGI foundations at Amazon after a rapid progression from Applied Scientist to Applied Scientist II. With an academic background from Carnegie Mellon and Georgia Tech and a decade-plus in computer science, he has driven practical gains—most notably a dynamic prompt optimization algorithm that cut LLM compute costs by over 25% and boosted task accuracy by 40% in enterprise agentic systems. His prior work at Google produced scalable pipelines for multimedia story generation and contributed to Photos features using automated prompting with Imagen, reflecting a blend of research rigor and production impact. Based in Bellevue, WA, he pairs systems engineering skills with applied ML research, and is comfortable taking ideas from prototype to cross-team deployment against real-world datasets and constraints. An understated strength is his track record of validating novel methods across diverse stakeholders, ensuring research translates into measurable operational improvements.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy, Computer Science, Doctor of Philosophy, Computer Science at Georgia Institute of TechnologySummer School, Public Economics, Summer School, Public Economics at Sciences PoMaster's degree, Electrical and Computer Engineering, Master's degree, Electrical and Computer Engineering at Carnegie Mellon University
English
Github Skills (6)
elections9
social-media8
web-application7
react6
hugo1
hugo-theme1
Programming languages (2)
Github contributions (5)
TheDanieLNK/thedanielnk.github.io
May 2020 - Apr 2024
Personal Website
Contributions:6 PRs, 67 pushes, 4 branches in 3 years 10 months
TheDanieLNK/smIleBM
Apr 2018 - Feb 2020
sample deep learning and computer vision project
Contributions:2 PRs, 14 pushes, 1 branch in 1 year 10 months
mobilenetmlppythoncaffe2unet-image-segmentation
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