Summary
Kyle Treleaven is an AI software engineer with 13 years of experience building production ML systems, cloud infrastructure, and real-time autonomous control software across Boeing, Amazon, Google, and Symbotic. He has deep hands-on expertise in training and deploying neural networks for both edge devices (wake-word detection) and large-scale cloud ML platforms, having authored modular workflow frameworks, multi-repo CI/CD pipelines, and DAG-driven training pipelines supporting dozens of active projects. His background includes PhD-level research in aeronautics and astronautics and applied work in multi-vehicle planning and control, bringing a rigorous, systems-first approach to ML engineering. Kyle has led small technical teams and collaborated closely with research scientists to bridge research and production, and he’s comfortable navigating secure, egress-restricted environments and low-power device constraints. Based in Somerville, MA, he pairs academic depth with practical production experience—an engineer who moves models from experiment to reliable service at scale.
13 years of coding experience
17 years of employment as a software developer
PhD Aeronautics and Astronautics, PhD Aeronautics and Astronautics at Massachusetts Institute of Technology
Master of Science - MS Electrical Engineering, Master of Science - MS Electrical Engineering at University of Pittsburgh Swanson School of Engineering
Computer Science, Computer Science at Harvard Extension School
English, Spanish