Summary
Jorge Ceja is a Machine Learning Engineer with nine years of experience building product-focused AI systems across startups and enterprises, currently developing generative AI pipelines for real-time 3D asset creation in gaming. He blends product, engineering, and design sensibilities to ship optimized deep learning models for web and mobile, including model compression and cloud-native deployments that cut costs and latency. His research background spans generative models for nonlinear dynamical systems and safety-aware black-box modeling, reflecting a rare mix of applied research and production engineering. As a freelance consultant and former Udacity mentor, he’s delivered solutions across consumer products, SaaS, robotics, and semiconductor-adjacent projects, often turning complex ML proofs-of-concept into deployable services. Based in Los Angeles, Jorge describes himself as an aspiring polymath—comfortable iterating from hardware-level constraints to high-level product decisions.
9 years of coding experience
1 year of employment as a software developer
Nanodegree, Autonomous Systems, Artificial Intelligence, Cloud Computing, Nanodegree, Autonomous Systems, Artificial Intelligence, Cloud Computing at Udacity
Bachelor of Science (BS), Electrical and Electronics Engineering, Minor in Computer Science (Dropped Out), Bachelor of Science (BS), Electrical and Electronics Engineering, Minor in Computer Science (Dropped Out) at California State University-Long Beach
Cohere AI Open Science
English, Spanish, Italian