Working in the R&D department developing the perception module of an actual autonomous (L4) vehicle:▪ Implementation of Deep Learning techniques for object detection.▪ Improvement of current state-of-the-art lane detectors.

▪ Projects were implemented following a Netflix microservice architecture along with the classical front and back stacks.▪ Angular and JAVA were used to develop the front-end and back-end respectively. Using as auxiliary tools JIRA and Jenkins.

▪ In charge of implementing a Machine Learning model for resource planning in chip’s production.▪ Python and Scikit learn were chosen to develop the whole application, allowing the optimization of design hours and computational expenses causing a huge drop in costs.

▪ Developed the software and control of a laser scan and a high resolution camera, which were used to take measurements of transparent parts from cars. ▪ C++, OpenCV and .Net were used to implement the project.▪ The scan had proved successfully in a real environment set up in the SEAT’s main factory.

▪ Direct contact with customers to get their feedback, while translating it into logical requirements to be performed.▪ Learnt ABAP in order to fix bugs in the Catalonia’s government internal application.