Engineering Evolution: Solving Super Mario with Genetic Algorithms
I completed a project that applied the principles of Darwinian evolution to a classic navigation problem: automating a playthrough of Super Mario Bros. using a Genetic Algorithm (GA)
Engineering high-performance, AI-integrated systems designed for scale and reliability. I focus on architecture-first solutions that bridge the gap between complex logic and seamless user experience, delivered with efficiency.
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I completed a project that applied the principles of Darwinian evolution to a classic navigation problem: automating a playthrough of Super Mario Bros. using a Genetic Algorithm (GA)
I recently served as a Frontend Software Engineer on the core team tasked with a complete architectural rebuild of the WSJ news article reader.
When **Powerade** launched a marathon series designed to engage tens of thousands of runners, the technical requirement was absolute: a platform that could facilitate registration, track performance, and manage a complex rewards economy without a single point of failure.
During my tenure as a **Full Stack Engineer** at Yellowme, I was presented with a challenge that would define my approach to modern software architecture: transforming the digital backbone of **FinBe (Financiera Bepensa)**, a heavyweight in the financial sector.
The mission was clear: take a high-growth startup’s legacy infrastructure and re-engineer it into a high-performance, real-time ecosystem capable of supporting millions of frontline workers.
During my time as a **Senior Full-Stack and DevOps Engineer at Mento**, I had the opportunity to lead a series of high-stakes architectural overhauls designed to eliminate technical debt, optimize performance, and drastically reduce operational overhead.