Sebastian Goodman
Staff Software Engineer at Google
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSebastian Goodman is a Staff Software Engineer with 13 years of experience building anything from deep learning frameworks to globally replicated storage systems. At Google since 2013, he helped deliver the replicated backend for Google Drive and most recently authored the codebase behind the PaLI vision-and-language model, blending production-grade engineering with cutting-edge ML research. He moves quickly from prototype to robust production, preferring practical solutions that scale and have broad applicability. An early contributor to ALBERT integrations, he brings both model-level ML engineering and large-scale systems expertise. Based in Los Angeles, he pairs an MS in Computer Science from USC with a track record of shipping complex, high-impact systems.
13 years of coding experience
2 years of employment as a software developer
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at University of Southern CaliforniaBachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at Montana State University-Bozeman
Stackoverflow
1,695reputation
322kreached
25answers
4questions
nginx
top-5%
Github Skills (17)
machine-learning10
tensorflow10
bert10
nlp10
python9
trainings9
modeling9
nginx9
mongodb6
ruby-on-rails6
mongoid6
memcached6
http-header6
ruby6
json6
Programming languages (6)
Github contributions (5)
google-research/albert
Oct 2019 - Feb 2020
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Role in this project:
ML Engineer
ML EngineerContributions:28 commits, 5 PRs, 1 branch in 4 months
Contributions summary:Sebastian primarily focused on modifying and integrating ALBERT models, evident in the code changes. They worked on adapting the model for different classification tasks, indicated by the `run_classifier_with_tfhub.py` file and general modifications for ALBERT integration. Their commits also suggest involvement in pre-training ALBERT models and running tests related to model functionality.
pytorchnlptransformerssupervised-learningsupervised
0x0539/tap.io
Aug 2012 - Apr 2013
Contributions:136 commits in 8 months
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