Michael Munn
Senior Software Engineer at Google
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Munn is a Senior Software Engineer and research-trained mathematician with 11 years of experience building and deploying machine learning solutions at Google and in enterprise settings. He blends deep academic rigor (PhD in Mathematics) with hands-on ML engineering, having led ML Solutions work in Google Research and the Advanced Solutions Lab to help customers scale models on GCP. His open-source contributions include practical notebooks for widely used Google Cloud ML training repos, such as adding embeddings and content-based recommendation examples to the GoogleCloudPlatform/ml-design-patterns and training-data-analyst projects. Michael also advises on AI instruction and curriculum design at SandboxAQ, translating complex research into effective training and customer-facing labs. Previously he taught and mentored at multiple universities, giving him a rare mix of pedagogy, published research, and production ML experience. Based in New York, he is skilled at turning theoretical insight into reproducible, cloud-native ML workflows and developer-facing educational artifacts.
10 years of coding experience
13 years of employment as a software developer
Master of Philosophy (M.Phil.), Mathematics, Master of Philosophy (M.Phil.), Mathematics at The Graduate Center, City University of New YorkBachelor of Science (B.Sc.), Honors Mathematics, Bachelor of Science (B.Sc.), Honors Mathematics at University of Notre Dame
English
Github Skills (13)
neural-network10
data-preprocessing10
jupyter-notebook10
machine-learning10
google-cloud-platform10
bigquery10
tensorflow10
embedding10
feature-engineering10
python10
gcp9
data-engineering9
data-representation9
Programming languages (3)
Github contributions (5)
GoogleCloudPlatform/ml-design-patterns
Mar 2020 - Sep 2020
Source code accompanying O'Reilly book: Machine Learning Design Patterns
Role in this project:
Data Scientist
Data ScientistContributions:38 commits, 6 PRs, 28 pushes in 5 months
Contributions summary:Michael contributed a new notebook to the repository titled "adding embeddings notebook", which provides an example of how to implement embeddings. The user also added a notebook that provides examples of feature crosses. There are minor typo fixes in the notebook as well.
machine-learning-bookmachine-learningpatternsdesign-patternso-reilly
GoogleCloudPlatform/asl-ml-immersion
May 2020 - Oct 2021
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
Role in this project:ML Engineer
ML EngineerContributions:7 reviews, 93 commits, 1 PR in 1 year 5 months
Contributions summary:Michael implemented and added structured labs and solutions, indicating a focus on applied machine learning. The commits include modifications to an end-to-end structured lab notebook, including data preparation steps using BigQuery to prepare the babyweight dataset. The user worked on preprocessing and filtering the dataset, and created the train and evaluation data sets in BigQuery.
pythondata-sciencegoogle-cloud-platformimmersionmachine-learning
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