Nathan spent the last decade building signal-processing systems for defense and commercial teams, most recently RF geolocation and device identification at Northrop Grumman. He now leads Diffio end-to-end: training denoising models, building cloud GPU pipelines, and shipping simple tools creators can rely on. The broader mission is outlined on the about page, and the current workflow is shown in how it works.

Strengths

• Speech restoration ML
• Cloud GPU inference
• Dataset & evaluation engineering
• RF signal processing (background)

Focus

Making clean audio effortless for scrappy teams and solo creators

Base

Colorado Springs, United States