I have worked in many different places, in startups, corporations, at the university and for the public administration. I have preference for multidisciplinary teams comprised of specialists from other areas such as Design, Marketing, Business and Operations where the Product Design / Lean Startup approach can be applied.
In the past working on designing and developing high availability eCommerce applications based on cloud and microservices. For the last four years, I have been working bringing Machine Learning techniques and solutions to small businesses demonstrating that these tools can solve everyday problems regardless of the size of their data.
Research Scholarship (2009 - 2010): Business process modeling and executable code generation on application servers at the University Research Center.
TICs Scholarship (2013): Economic acknowledgement granted to students with outstanding performance studying the last stage of IT careers.
FONSOFT Funding (2014): Thesis accepted in FONSOFT, a government program that funds interesting projects that could be used in the public administration for improving the efficiency of state processes.
A four-month specialization course about data selection, processing, analysis, and visualization, we learned about developing and training of predictive models based on supervised and unsupervised machine learning algorithms using the SciPy Stack.
Final Project: Guest classification model for a hotel chain.
A four-month specialization course about theoretical fundamentals, training and convergence of neural networks. Implementation of dense, convolutional and recurrent architectures. Applications on text, image, audio, and video.
Final Project: Intent-Based Bot.
Designing, development, and implementation of an IoT platform to support the different projects of the Startup. I have worked on MediBox, a device designed for monitoring vital parameters of Covid19 patients.
Time Series model training to predict honey production.
Tools used: Flask, InfluxDB, Grafana and AWS.
In the courses of Artificial Intelligence and Cloud Architect on Machine Learning Engineering modules where we have taught how to put models into production in different ways using AWS tools and containers.
Designing, development, and implementation of a data pipeline on AWS for cleaning 20M+ conversations daily.
NLP and Topic Modeling application for intent discovering.
Training and serving of classification models to predict intent and keywords in the conversations.
Tools used: SciPy, spaCy, Keras, TensorFlow, PyTorch, MongoDB, ELK and AWS.
Redesigning and developing of the processes and platform of the strategic business unit of Wedding Lists.
Base architecture implementation on AWS.
Integration with branch offices systems, payment gateways, ERPs and Mobile through backend services written in SpringBoot and Node.js.
Development of forward integrations with shipping and post-sale services through REST APIs using Java and MongoDB.
OAuth2 implementation, developing of the reports module on a REST API using Java and MySQL and integration with external services. Deploying on AWS EC2.
Designing and developing of the quotation negotiation process and its implementation on a REST API using Java and MySQL. Data extraction, transformation, and load from external sources using Pentaho BI. Deploying on AWS EC2.
Designing and developing of web applications to support the organization business processes using LAMP stack.
Migration of an education platform from one application server (JBoss) to another (Weblogic) and from one Database (MySQL) to another (Oracle).
Development of a web application that was used in the Intranet, an access control system for the scholars of the university laboratories using LAMP stack.
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