Jeremy Lane

Senior Applied Scientist at Amazon

New York, New York, United States
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Summary

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Senior
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Top School
Jeremy Lane is a Senior Applied Scientist in New York with 11 years of experience building foundation models and shipping flagship AI agent systems at Amazon. He blends deep mathematical training (PhD in Mathematics) and postdoctoral research in geometry and mathematical physics with hands-on ML engineering to deliver production agent architectures, monitoring, and multiturn evaluation pipelines for advertiser-facing products. Jeremy has led science teams that translated novel research into scalable ad targeting, measurement, and planning systems, and he continues to drive model and systems delivery as a core contributor on foundation-model efforts. Comfortable moving between abstract math and practical engineering, he has a track record of publishing research, organizing international workshops, and mentoring students who have gone on to publish.
code11 years of coding experience
job6 years of employment as a software developer
bookDoctor of Philosophy - PhD, Mathematics, Doctor of Philosophy - PhD, Mathematics at University of Toronto
bookBachelor of Science Honours, with High Honours in Mathematics - BSc, Mathematics, Bachelor of Science Honours, with High Honours in Mathematics - BSc, Mathematics at University of Regina
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Github Skills (18)

autoencoder8
ssreflect7
matrix-factorization7
implicit7
collaborative-filtering7
trains6
mod-manager6
filtering5
recommender-system5
datasets5
machine-learning5
recommendation-system5
pytorch4
python4
mixture-of-experts3

Programming languages (2)

Jupyter NotebookPython

Github contributions (5)

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lanej5/bm

May 2018 - Mar 2022

A deep autoencoder that pre-trains weights with Restricted Boltzmann machines
Contributions:31 commits, 25 pushes, 1 branch in 3 years 10 months
pytorchautoencoderssreflecttrainsmod-manager
lanej5/MNIST-GAN

May 2018 - May 2022

Contributions:45 pushes, 1 branch in 4 years 1 month
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Jeremy Lane - Senior Applied Scientist at Amazon