About Denny Schaedig

Denny Schaedig is a machine learning engineer who designs, trains, and ships ML systems end to end, from data pipelines and distributed training to model packaging, serving, and deployment. A Colorado native, he is based in Summit County.

He came to machine learning through neuroscience. While earning a B.A. in Neuroscience at the University of Colorado Boulder, he focused on how the brain learns, forms memories, and uses what it has learned, and coursework in computer science and mathematical models of cognition drew him toward AI. In 2018, in the Banich Lab, he began applying computer vision and deep learning to 4D fMRI data, work that became BOLDnet (originally KleinNet). He went on to earn an M.S. in Artificial Intelligence and Machine Learning from Colorado State University Global in 2025.

Since December 2022 he has worked remotely as the NeuroImaging Engineer at the Laboratory for Child Brain Development at Washington University in St. Louis, a role focused on machine learning and software engineering. There he architected a HIPAA-compliant AWS HPC environment and built HRfunc, an open-source fNIRS analysis package published in Neurophotonics. He also founded Rocky Mountain Digerati, an independent applied-ML lab where he builds LLM-agent systems and ML for avalanche safety: the open Rocky Mountain Snowpack dataset, the snowGAN generative models, and AvAI, a backcountry check-out safety app. His open-source cognitive architecture, Maxim, explores persistent memory and reward learning for LLM agents and robots.

Outside of work, he teaches skiing as a PSIA-certified instructor and is learning to snowboard.