Software engineering, with room to keep learning
I’m Jordon Taylor, a senior studying Computer Science at the University of Florida. I expect to complete my BS in December 2026 and am pursuing new-graduate software engineering opportunities.
My projects connect algorithms and implementation: reproducible reinforcement-learning experiments, approximate similarity search, local model inference, and backend tests for a collaborative application. I enjoy understanding the assumptions behind a system as much as connecting its parts.
The work I take ownership of
On Gradient Gators, I lead training and integration within a five-person senior research team. My implementation work includes survivability witnesses, frozen scenario snapshots, deterministic schedules, PPO pilot infrastructure and CI.
Other projects have given me a different set of constraints: making approximate search understandable in a web interface, matching a Unity drawing pipeline to a model’s input, and isolating a database so backend behavior can be tested predictably.
Experience that informs how I work
I currently work as a Geek Squad Consultation Agent. Troubleshooting and customer-facing technical communication have given me a useful perspective: understand the problem, explain the options clearly, and connect a technical decision to the person it affects.
Software engineering is the direction I’m building toward. My current work provides context for that goal, alongside the implementation and collaboration demonstrated in my projects.
I also created and maintained a website for Next Level Achievement. That project gave me an earlier opportunity to turn a real organization’s needs into a working website.
Foundations and interests
My project work includes Python, C#, C++ coursework, NumPy, Flask, SQLAlchemy, pytest, Git, CI, Unity and ONNX integration. In reinforcement learning, I work with Gymnasium, Stable-Baselines3 and PPO.
I’m interested in software architecture, AI reliability and evaluation, AI safety, and prompt engineering. My hands-on AI experience is in reinforcement-learning infrastructure and model integration; these broader interests are areas I want to keep developing.