Sean Morgan
Senior Director at Palo Alto Networks
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSean Morgan is a Senior Director based in San Jose who blends nine years of hands-on AI/ML engineering with strategic leadership in AI security, currently shaping product and architecture at Palo Alto Networks after leading Protect AI as Chief Architect. He has deep practitioner experience across cloud ML at AWS (SageMaker lead), adversarial ML via the Adversarial Robustness Toolbox, and core TensorFlow ecosystem work as SIG lead and contributor to tensorflow/addons. Sean’s background spans research and production—DARPA-focused solutions, large-scale model deployments, and probabilistic forecasting—enabling him to bridge research, production engineering, and governance. An active open-source maintainer, he contributes tests, docs and model tooling that improve TensorFlow extensibility and reproducible SageMaker examples. He also advises at a policy level through roles like the Coalition for Secure AI, bringing technical rigor to industry-wide AI safety discussions. Uncommonly for a leader, he remains a frequent committer on low-level ML libraries, retaining a coder’s attention to detail while driving cross-functional strategy.
9 years of coding experience
10 years of employment as a software developer
Bachelor of Science Chemical Engineering, Bachelor of Science Chemical Engineering at University of MarylandMaster of Engineering Electrical Engineering, Master of Engineering Electrical Engineering at University of Virginia
Github Skills (19)
python10
artwork10
testing10
machine-learning10
numpy10
amazon-sagemaker10
tensorflow10
jupyter-notebook10
pytorch9
deeplearning-ai9
neural-network9
deep-learning9
keras9
scikit8
jax8
Programming languages (8)
Github contributions (5)
tensorflow/addons
Nov 2018 - Dec 2022
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
Role in this project:
ML Engineer
ML EngineerContributions:20 releases, 93 reviews, 405 commits in 4 years 1 month
Contributions summary:Sean's commits primarily involve modifying and testing code within the `tensorflow/addons` repository, which focuses on extending TensorFlow functionality. Their contributions include changes to unit tests, such as the `LazyAdamOptimizerTest` and `SkipGramOpsTest`. They also implemented changes in areas related to layers and text processing, aligning with machine learning model development. The user has updated documentation for the library as well.
python2-xdeep-learningaddonssig
aws/amazon-sagemaker-examples
Nov 2020 - Dec 2022
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Role in this project:ML Engineer
ML EngineerContributions:27 reviews, 28 commits, 37 PRs in 2 years 1 month
Contributions summary:Sean primarily contributed to the development and improvement of machine learning examples within the Amazon SageMaker environment. Their work included adding features to estimators for improved model training, such as framework versioning in a scikit-learn estimator, and adapting existing examples to use a more modern SDK. The user also provided examples for training and deploying models using JAX and synthetic datasets, furthering the use of the repository. Their contributions extended to updating existing notebook examples.
pythonjupyter-notebooktrainingawssagemaker
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