[🇬🇧] I'm an Acoustical Engineer who derived in Software Engineering, large-scale Backend development and Machine Learning. I've worked as individual contributor as well as technical leader for multiple teams in all the previous areas. The industries I've worked in range from FinTech and MarTech to AI applied to audio.

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Soy un Ingeniero Acústico devenido en Ingeniero de Software, desarrollador Backend e Ingeniero de Machine Learning. He trabajado como desarrollador y también como líder técnico en todas las áreas anteriores, en industrias como FinTech, MarTech e IA aplicada a audio.

an AI project for voice cloning in a consulting company, presently putting in into production for the first clients! 🎉🚀

I collaborated in creating a data science product for Marketing Mix Modeling (MMM), in Python, using Poetry, Jax and Haiku. I also designed and implemented several MLOps-focused refactors in another product, a daily campaign optimizer. My contribution helped make product demonstrations faster and more useful, keep the projects more maintainable in the long term, and introduced DevOps practices which made the development fluid.

The tech stack I used was Python-based, using Jax for JIT compilation, Haiku for model implementation, AWS SageMaker for running processing jobs, Jupyter Lab for hosting notebooks, Docker for containerization, GitHub Actions for CI/CD workflows, FastAPI for exposing training and inference APIs:

• I worked with a multinational payment processing company, building modern distributed APIs in Java and SpringBoot for their legacy backends.
• I worked at a startup which aimed to integrate multiple bank accounts, credit/debit cards and simplify getting access to cryptocurrencies. There, I collaborated in creating the microservices for the cryptocurrency exchanges, using Kotlin and SpringBoot this time, with Kafka, AWS S3 and SQS, and lots of other fun tools.

As part of a mandatory internship in my university, I led a team of Jr and trainee developers in a voice cloning project for Buenos Aires (porteño) Spanish. I worked as Technical Leader because already had some years of experience. In a daily basis, I was able to train other interns, introduce Software Engineering practices, CI/CD, clean code, OOP principles and systems design. After three months we were able to show useful results and the project remained stable after I finished my internship.

The tech stack was Python 3, PyTorch for the neural networks, GitHub Actions for CI/CD, Docker for containerization, AWS for training and hosting models, FastAPI for exposing APIs, and so on: