Kelechi Uhegbu is a Senior Staff Machine Learning Engineer based in the San Francisco Bay Area with eight years of experience building and securing large-scale ML systems. After progressing from machine learning engineer to senior staff at Palo Alto Networks, they blend applied research in federated learning from Stanford SAIL with hands-on security and cloud experience from internships at Amazon and Northrop Grumman. Their work spans production ML, federated decision trees, and security automation—having automated remediation workflows across thousands of services and vulnerabilities. Comfortable navigating academia and industry, Kelechi has co-authored research and is currently advancing ML models for medical imaging and SHG tasks, bringing rigorous research methods to operational security and ML products.
8 years of coding experience
3 years of employment as a software developer
High School Diploma, High School Diploma at Del Norte High School
Bachelor of Science - BS, Bachelor of Science - BS at Stanford University
Contributions:4 PRs, 26 pushes, 6 branches in 15 days
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