Experience

2024-09/actuality

AI tech lead

Bravent

-

Remote

AI Tech lead. Technical leadership, development supervision and collaboration in the correct management of technical projects. Proposal of new solutions.

Responsibilities

  • Technical Leadership.
  • Technical Decision Making: appropriate technologies.
  • Propose new solutions in the area/innovation.
  • Develop SW established standards, high complexity, short deadlines.
  • Development Supervision.
  • Collaboration for the correct management of technical projects.
  • Technical Risk Assessment
  • Assist in the resolution of technical issues.
  • Clear and effective communication
  • Keeping up to date with the latest technologies and trends in the field

Key Accomplishments

  • I haven't had time to achieve any significant accomplishments yet.
  • Python
  • Pytorch
  • HuggingFace
  • Azure

2022-09/2024-09

Machine Learning Engineer

Sener

-

Tres Cantos, Madrid

Machine Learning Engineer, vision algorithms development for autonomous vehicle and leadership in RAG system to obtain documentation information

Responsibilities

  • Development of the set of vision algorithms for autonomous vehicle.
  • Leadership in the development of RAG system to obtain documentation information.

Key Accomplishments

  • When working on an autonomous vehicle everything has to go on an embedded device, which is not as powerful as a normal computer. So I optimized the neural networks with TensorRT, making the inference time and the necessary VRAM memory much lower, ensuring the real-time operation of the autonomous vehicle.
  • Development of a dataset of realistic synthetic images to train the networks for the autonomous vehicle, creating images in different environmental conditions, making the neural networks more robust.
  • Implementation of startup scripts for all the libraries and programs of the autonomous vehicle device. Before only one person knew how to install everything, now anyone can start the system.
  • Promotion of a colleague
  • Mentoring of interns and juniors
  • Python
  • Pytorch
  • HuggingFace
  • TensorRT
  • Nvidia Jetson

2017-10/2022-07

AI and electronic engineer

Arquimea

-

Leganés, Madrid

AI, HW and FW development.

Responsibilities

  • Implementation of detection algorithms for UAV.
  • Development of a pilot algorithm for geopositioning without GPS.
  • Leadership of UAV HW and FW development.

Key Accomplishments

  • With the implementation of detection algorithms for UAV, we avoided having to buy a device that did such detection, saving a cost of €2000 per unit.
  • When I arrived, the HW and FW of each of the UAVs and ground stations was different, which meant that there were several teams developing the same functionality, in different ways. I unified the HW of the UAVs and ground stations, which reduced the cost of PCB manufacturing. It also allowed to create a common low-level FW, having to change only the high-level part, avoiding duplicate developments.
  • In electronic warfare environments, it is common to disable the GPS, which is lethal for UAVs, as they cannot geoposition. With the pilot algorithm for geopositioning without GPS, we managed to have a competitive advantage against our competitors.
  • Python
  • Pytorch
  • YOLO
  • Altium
  • STM32
  • C

2014-05/2017-10

Electronic Engineer

Indra

-

Torrejón de Ardoz, Madrid

HW and FW development.

Responsibilities

  • FW development of autonomous helicopter control PCB.
  • Maintenance of autonomous helicopter PCB HW.
  • HW development of PCB with sensors for a fighter.

Key Accomplishments

  • Nobody wanted to take charge of the FW of the autonomous helicopter control PCB, which made the project progress very slowly. I took charge of the FW, so the project progressed much faster.
  • When I arrived, the startup tests of the PCBs were done by hand, since they were designed by the engineers who designed them and only tested them in the design phase. But when the project was in production, every time new PCBs were manufactured, their tests were very slow because they had to be done by hand. In the PCBs I developed, I implemented test wiring and test FW, so that the test of the PCBs was done automatically, making that when the project was in production, the tests of the PCBs could be done much faster and also could be done by more people, because it was not necessary to have personnel with a certain minimum knowledge.
  • Altium
  • C
  • Eclipse

2013-01/2014-05

Intern

Indra

-

Torrejón de Ardoz, Madrid

Help project manager in project management. HW and FW development.

Responsibilities

  • Help project manager in project management.
  • Design tests for starting communications PCBs for air traffic controllers.
  • HW and FW design

Key Accomplishments

  • Design and documentation of tests for starting communications PCBs for air traffic controllers.
  • Repair of PCBs for air traffic controllers.
  • Altium
  • C
  • MPLAB

Continue reading

DoLa – Decoding by Contrasting Layers Improves Factuality in Large Language Models

DoLa – Decoding by Contrasting Layers Improves Factuality in Large Language Models

Have you ever talked to an LLM and they answered you something that sounds like they've been drinking machine coffee all night long 😂 That's what we call a hallucination in the LLM world! But don't worry, because it's not that your language model is crazy (although it can sometimes seem that way 🤪). The truth is that LLMs can be a bit... creative when it comes to generating text. But thanks to DoLa, a method that uses contrast layers to improve the feasibility of LLMs, we can keep our language models from turning into science fiction writers 😂. In this post, I'll explain how DoLa works and show you a code example so you can better understand how to make your LLMs more reliable and less prone to making up stories. Let's save our LLMs from insanity and make them more useful! 🚀

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Subtitle generator for videos in the language you want. Also, it puts a different color subtitle to each person

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Do you want to apply AI in your project? Contact me!

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Use this locally

Hugging Face spaces allow us to run models with very simple demos, but what if the demo breaks? Or if the user deletes it? That's why I've created docker containers with some interesting spaces, to be able to use them locally, whatever happens. In fact, if you click on any project view button, it may take you to a space that doesn't work.

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Do you want to apply AI in your project? Contact me!

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