Jon Morra
Chief AI Officer at Amplify.LA Capital
El Segundo, California, United States
Summary
👤
Senior🎓
Top SchoolJon Morra is a strategic AI and data leader with nine years of experience building and scaling data-driven products from 0-to-revenue, now serving as Chief AI Officer at Zefr where he oversees 25+ engineers and scientists and drives over 2 billion monthly inferences across major social platforms. He combines deep technical roots—from contributing to the Vowpal Wabbit ML codebase and improving Java build/testing—to product-facing roles that launched the industry’s first brand safety offerings on TikTok and Meta. Jon has repeatedly moved prototype ideas into production using diverse tooling (PyTorch, TensorFlow, Metaflow) and multilanguage stacks, and he’s built responsible AI revenue lines while evangelizing impact to C-suite and industry audiences. A former founder and biomedical engineer with a PhD pedigree, he brings a rare blend of hands-on engineering, research rigor, and go-to-market product craft that helps teams ship practical, high-scale ML solutions.
9 years of coding experience
18 years of employment as a software developer
Johns Hopkins UniversityUniversity of California, Los Angeles
English
Github Skills (11)
unit-testing10
javas10
machine-learning10
java10
test-automation10
elearning10
active-learning9
searching9
cprogramming-language9
c-language9
cpp8
Programming languages (4)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Jun 2017 - Aug 2017
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:24 commits, 8 PRs, 37 comments in 1 month
Contributions summary:Jon's contributions primarily focused on improving the Java build process and ensuring the stability of the codebase through testing. This involved modifying Makefiles, addressing code reviews to enhance code quality, and updating Java project dependencies. Furthermore, the user added and modified unit tests, particularly related to CSOAA, showcasing a focus on testing machine learning functionalities within the project. The user also worked on ensuring that Java responses were serializable for better data handling and multipass support within the Java layer.
hashingtechniquescpppythonactive-learning
IABTechLab/Brand-Suitability-Test-Benchmarks
Apr 2021 - Jun 2022
Media content that has been human labeled according to the GARM standard.
Contributions:1 review, 46 commits, 3 PRs in 1 year 1 month
machine-learninggarm
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.