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David L.DL

David L.

Embedded Software Developer | IoT

€450/day
1 project
Aubusson, FR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About David

Passionate about electronics and computer science from a young age, I chose to orient my professional project to combine practice and theory. Thus, I started with the IUT GEII of Brive, and continued in engineering school in Electronics and Industrial Computer Science at INSA Rennes.
Curious by nature, I familiarized myself with the world of business by participating in FabLab19 where I also had the opportunity to learn about CAD for 3D printing and laser cutting.
  • English

    Fluent

  • French

    Native or bilingual

Can work on-site
Aubusson (up to 50km), Grenoble (up to 50km)

Experience

  • BIC
    Embedded firmware engineer
    TECH
    February 2023 - Today (3 years and 4 months)
    Grenoble, France
    Firmware development on ST target (STM32F7/ STM32H7/BLUENRG2)
    Memory placement optimization
    Firmware development of the BLE (Bluetooth Low Energy) module
    Contact with labs for BLE certification
    Implementation of a multi-project continuous integration system
    Development of scripts to create a common code base
    Integrations with ST tools (STM32CubeMX/ Package creator)
    Implementation of means of testing and code quality analysis
    Jenkins/Gitlab integrations
    STM32 Bluetooth Low Energy Gitlab Gitlab CI/CD Jenkins C Python
  • ALSTOM
    Embedded computer engineer
    TRANSPORTATION
    January 2021 - February 2023 (2 years and 1 month)
    Grenoble, France
    Testing and integration of a real-time system embedded in the railway sector (SIL4):
    Define test strategies to ensure coverage of requirements
    Implementation of tests:
    ADA/Python (Pytest)
    Writing associated documentation
    Embedded Systems Python Ada CI/CD Jenkins
  • Thales
    AI Trainee Engineer
    DEFENSE AND MILITARY
    February 2020 - August 2020 (6 months)
    Cholet, Pays de la Loire, France
    • Development and implementation on an embedded system of a convolutional neural network (CNN) for voice detection of keywords.
    • The major challenge of the project is to combine a high level of accuracy with limited computing and memory capacity.
    Main tasks:
    ➔ Training: Tensorflow
    ➔ Inference: model development with numpy
    ➔ Testing the limits of the model
    ➔ Porting to Ultra96 FPGA card
    ➔ Remote collaboration with another team
    ➔ Algorithms: CNN, MLP
    ➔ Characteristics: MFCC
    AI Deep Learning Python

Reviews

5.0

Out of 1 rating

P

Philippe

SIG ADEXIA

Reviewed on 4/2/2021

David has been efficient and serious. He immediately understood our need and was able to provide relevant advice and ideas. Although specialized in C and python, he was able to broaden his field of skills so that the solution is adapted to our expectations.

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Education

  • Study semester
    École de technologie supérieure (ÉTS)
    2019
    Dans le cadre de la formation d'ingénieur, j'ai saisi l'opportunité de faire mon semestre à l'étranger à l'ÉTS de Montréal qui a l'avantage de mettre l'accent sur l'aspect pratique. J'ai profité du choix libre des cours pour étendre mon champ de compétences. • ELE674 : Systèmes embarqués avancés Conception d'un système d'exploitation embarqué pour drone Parrot, fondé sur un OMAP3630 (Arm Cortex-A8). • LOG635 : Systèmes intelligents et algorithmes Développement de différents algorithmes d'intelligence artificielle pour exploiter les possibilités offertes par le robot Cozmo. • LOG645 : Architectures de calculs parallèles Conceptions d’algorithmes parallèles et techniques d'analyse de performances Bibliothèques : OpenCL MPI CUDA • GTI770 : Systèmes intelligents et apprentissage machine Réseaux de neurones, arbres de décisions, SVM... Bibliothèques : TensorFlow et OpenCV • GTI611 : Réseaux de communication IP Analyse et conception d’architectures réseau de communication IP.
  • Engineering degree
    INSA Rennes - Institut National des Sciences Appliquées de Rennes
    2020
    La formation en section EII m’a permis d’acquérir des connaissances pluridisciplinaires solides dans les domaines de l’informatique industrielle, de l’électronique, du traitement du signal et de l’automatique.

Skill set

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