Joberth R.

Full-stack Product Engineer

Full Stack Developer
9/1/2021 - Present

Served as a Full Stack Developer for an agricultural consultant application offering farmers insights into their crops. Developed technical expertise in Grafana, Prometheus, Docker, and Kubernetes. Leveraged InfluxDB and MongoDB for database management. Created user interfaces using React Native and Angular, and built backend services with NodeJS and Flask.

Development Analyst (Analytics)
7/1/2021 - 9/1/2021

Developed solutions utilizing machine learning and deep learning models for network vulnerability recognition, leveraging expertise in Python. Utilized RabbitMQ for efficient messaging queues and Docker for containerization to ensure scalable and reproducible environments.

Intern/Backend Developer
3/1/2021 - 6/1/2021

Focused on the development of an application for managing Giga Candanga's clients, specifically on the backend. Developed proficiency in Golang, implementing various backend functionalities and ensuring optimal performance and scalability. Utilized tools and frameworks pertinent to backend development, enhancing the application's efficiency and reliability. Additionally, contributed to code maintenance and version control, ensuring seamless integration and deployment of new features.

Intern/Full Stack Developer
1/1/2020 - 3/1/2021

Developed the main management platform for smart locks, utilizing Angular for frontend development and Spring Boot for backend services. Enhanced technical expertise in JavaScript for the client-side application and Java for server-side logic. Demonstrated proficiency in creating a robust, scalable, and user-friendly platform, ensuring seamless integration between frontend and backend components. Utilized Spring Boot to manage system security, data processing, and business logic, while Angular was employed to deliver a responsive and efficient user interface.

Researcher
1/1/2020 - 3/1/2020

Gained specialized knowledge in software product lines, focusing on the evolution of UML behavioral models for a reliability calculation tool. Collaborated with two other software engineering students to enhance model accuracy and tool robustness. This involved refining UML diagrams to better represent system behavior and ensure reliability metrics were accurately computed, demonstrating expertise in both theoretical understanding and practical application of software engineering principles.

Researcher
2/2/2019 - 3/1/2020

Led a research project focused on developing a software solution using deep learning techniques for the classification of suspicious audio files extracted from electronic devices in the context of drug trafficking. Gained extensive experience in neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Utilized TensorFlow and Keras frameworks for building and training deep learning models. Employed tools like Python and libraries such as LibROSA for audio processing and feature extraction. Conducted data preprocessing, augmentation, and model evaluation to ensure high accuracy and reliability. Facilitated collaboration and code management through Git for version control, ensuring seamless integration and project progression. Worked in partnership with an academic institution and law enforcement agencies to align technical solutions with practical investigative needs.

Software Engineering at University of Brasília
2016 - 2021