I'm a Software Engineer with a passion for building solutions that marry technical excellence with human-centered design. With experience in full-stack development (React, Node.js, Swift) and AI engineering (TensorFlow/Keras), I thrive in roles where I can bridge the gap between complex technology and real user needs. My approach combines leadership (Agile/SCRUM), problem-solving (LEAN methodologies), and a relentless focus on impact.

Languages
I'm proficient in multiple programming languages, from system-level (C/C++)
to AI development (Python) and mobile apps (Dart/Swift). I choose the best tool for each challenge:
Frameworks & Technologies
Frameworks are my force multipliers. Whether building AI models with TensorFlow,
crafting responsive UIs with React, or delivering mobile apps via Flutter,
I choose technologies that deliver results efficiently:
React
Flutter
Firebase
Node.JS
Tensorflow
Vercel
Supabase
Git
Postman
Pandas
Matplotlib
Tailwindcss
Unity
Experience

GE AEROSPACE
Software Engineer Intern
As a Software Engineer Intern in the LEAN SUMMER EXPERIENCE, I developed automation tools to optimize audit workflows,
reducing processing time by 51%. Designed a standardization prototype that contributed to my team’s
2nd Place finish in the program. Technologies: VBA, LEAN frameworks.

Why Transformation
Jr. Full-Stack Developer
Built and maintained client websites (e.g., CEPA, Make-A-Wish) with custom WordPress plugins and optimized UX.
Automated workflows using Zapier and ensured site stability through performance updates.
Technologies: WordPress, PHP, JavaScript.
Projects
HiTec Register
Check repository!
Large-scale academic event management system developed for Tec de Monterrey's
HiTec conference. The platform proved its robustness by handling 600+ concurrent users
during registration peaks with zero downtime. I implemented a CSV bulk registration
system capable of managing 1,500+ activity slots, along with a streamlined authentication method
that reduced access time to just 3 seconds using student ID validation. The architecture featured:
intelligent scheduling to prevent overlaps (limiting to 1 activity per hour), real-time updates via
Supabase, and optimized Vercel deployment ensuring sub-2-second response times even under peak load.
Carssification AI
Check repository!
AI model achieving 94.7% precision in classifying 40 car part types.
Used ResNet50 transfer learning with custom dense layers (512-128 neurons) and
dropout regularization. Optimized via early stopping, reducing overfitting by 23%
from initial architecture.
Contact
Let's build something amazing together! Whether you have a project in mind,
want to collaborate, or just talk about software development, I'd love to hear from you.
Coffee chats are always welcome too!