Birdbox
Raspberry Pi-based bird call identification using BirdNET Pi.
I'm a
Aspiring AI/ML engineer with a background in systems, a passion for learning, and a portfolio of hands-on, real-world projects.
I'm a Computer Science student with a professional background in infrastructure, DevOps, and high-stakes operations, now fully focused on building a career in AI and machine learning. I bring a deep understanding of distributed systems, Linux environments, and data pipelines to my evolving work in intelligent systems and model-driven applications.
My recent projects center on AI/ML prototyping, from classical models to transformer-based pipelines, with the goal of bridging the gap between academic models and production-ready tools. I’m especially excited about intelligent agents, LLMs, and applying machine learning to hard, unsolved problems.
With a strong foundation in Python and C++, I’m adept at building scalable, efficient systems that leverage the latest advancements in AI. I thrive on challenges and am passionate about creating solutions that make a real impact.
Technical foundation built across DevOps, systems engineering, and a growing specialization in applied AI/ML.
Engineer with 7+ years of experience in technical operations, DevOps, and distributed systems — now focused on applied AI/ML and intelligent agent systems. Currently completing a B.S. in Computer Science with a deep dive into model prototyping, LLM pipelines, and data-driven engineering.
Versatile technologist with a strong foundation in Python, Bash, Linux, and performance engineering. Known for shipping stable systems under pressure and now applying that discipline to AI/ML systems, from classical models to transformer pipelines and inference workflows. Passionate about LLMs, intelligent agents, and turning data into solutions.
Edgio, Scottsdale, AZ
Early Warning Services, Scottsdale, AZ
Endurance International Group, Tempe, AZ
Arizona State University
Focused on algorithms, machine learning, and intelligent systems.
Maricopa Community Colleges
Completed with 4.0 GPA. Transitioned from systems engineer to full-time CS student.
A selection of hands-on AI/ML projects built with real-world data, practical tooling, and a focus on learning through implementation. Each project explores a key concept from classical models to LLMs and agent-based systems.