Hi, I'm Jarrod Barnes. I'm an Applied ML engineer based in New York. My current work focuses on continual learning and reward modeling for AI agents.
Previously, I founded Arc, where we built ATLAS, a continual learning framework deployed with F500 enterprises. Before that, I built RL environments and distributed training infrastructure at NEAR.
I studied learning design at the University of Illinois Urbana-Champaign (UIUC), researching how to design optimal learning environments and the science of skill acquisition. I left to found Arc, where those concepts became the foundation for how we teach agents to learn. Before ML, the throughline in my career has been to maximize human potential and help people get from where they're at to where they want to go. I was an Assistant Professor at NYU, an early-stage investor at Emerson Collective, worked in the NFL for the Los Angeles Rams, and began my career as a college football coach at Ohio State and Clemson.
I build AI systems that learn and adapt from experience.
My research pursues this through three directions: 1. continual learning, from hybrid models of in-context learning to self-improvement to new model architectures; 2. reward systems, optimal learning signals and machine-actionable feedback to maximize learning per token and intelligence per watt; and 3. adaptive RL environments, enabling environments to be world models themselves, optimizing desirable difficulty and learning curriculum for models to build, refine, and adapt skills over time. More on this