Summary
Nathaniel Burnham is a Staff Machine Learning Engineer with 11 years of experience building production ML systems, embedded vision pipelines, and robotic platforms across startups and research labs. He has led architecture and execution from device-to-cloud—shipping on-device TensorFlow Lite models, Android data pipelines, and scalable Kubernetes-backed ML services that processed billions of images monthly. As a founder and early employee multiple times, he blends product-driven engineering with hands-on implementation, having built agent frameworks, dynamic internal tooling, and annotation systems that dramatically reduced labeling costs. His background in embedded systems, CAD and custom electronics informs a pragmatic approach to deploying ML in constrained hardware, while his teaching and leadership roles reflect strong mentorship and cross-functional collaboration. Based in Los Angeles, he repeatedly turns prototypes into shipped products and is comfortable writing everything from C++ TensorFlow ops to full-stack TypeScript applications.
11 years of coding experience
9 years of employment as a software developer
Master of Science in Engineering Computer Engineering, Master of Science in Engineering Computer Engineering at Mercer University