Software Engineering for AutoSAR team and Advance Safety & User Experience Division, developing software products and enhancing product quality and customer satisfaction based on SCRUM methodology.

Programmed an Autonomous Mobile Robot (AMR) with an integrated gripper for specific pick and place deliveries. For the manipulation system, was used a limit switch as presence flag and two servos for the gripper in order to pick up and delivered ArUco cubes on a designed area implemented on STM32F103c8t6 at low-level code using serial communication ROS nodes for desired tasks. The navigation system consisted of a camera lidar, odometry, ArUco markers, computer vision and bug 0 algorithms implemented on a Jetson Nano using ROS for real-time tasks.

Worked as a Data Analyst and Back-end Developer, using one of their databases SCINCE 2020. I worked on analysing and cleaning up the data to train an NLP model to fulfil queries on demand by a user via a chatbot for personalized attention to finally visualize the results on the dynamic map of the Nuevo Leon region using a Full-Stack web development.

Programming a Self-Driving robot for track detection and line follower using computer vision, implementing CNNs to identify traffic signals, OpenCV to identify traffic light colors and rail identification for motion planning using a PID controller for motion correction. Implemented on an Nvidia's Jetson Nano using ROS to manage resources and tasks in real-time. Additionally, I worked in the development and simulation of a pick & place task for a robotic arm using Gazebo and Rviz as simulation and 3D visualization environment respectively for real-time simulation implemented with ROS as well.

With Intel as an embedded software engineer, I had the opportunity to learn about FPGAs, SoC, CPU architecture, pre-silicone process, firmware, SW and HW integration. First project worked programming FPGAs using Verilog, VHDL, and assembly and using Processing 3 as a game display programmed in C. Second project worked with SoC, where I programmed the microcontroller Atmega328p using C and C++ in low-level code and with Raspberry Pi PyQT5 as GUI.