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Mathieu GrossoMG

Mathieu Grosso

Machine Learning Engineer & Software Engineer

€750/day
Paris, FR
3-7 years

Average response time: 1 hour

About Mathieu

Etudiant en double diplôme à HEC Paris et aux Mines paris. Je suis également titulaire d'un Master 2 en informatique appliqué à l'intelligence Artificielle.

je suis passionné par la data science et l'intelligence artificielle ainsi que leur application à l'industrie. Mon champ de compétence comprend: maitrise de python et des bibliothèques de deep learning et de machine learning, maitrise de SQL et spark. J'ai aussi des compétences en développement Front end notamment react, css, html et suis très intéressé par travailler dans ce secteur.
  • English

    Native or bilingual

  • Spanish

    Fluent

  • French

    Native or bilingual

  • Japanese

    Basic

Can work on-site
Paris (up to 50km)

Experience

  • bnpparibas
    Data Scientist (NLP researcher)
    TECH
    March 2022 - September 2022 (6 months)
    Paris, France
    Worked on Multilingual Neural Machine Translation models :
    - Wrote a paper on a new domain adaptation approach for Multilintual NMT models (M2M100 & mBART50).
    - Build Operational Pipeline to do training of new Multilingual NMT models
    - Made benchmark between multilingual NMT models and bilingual NMT models.
    - Worked with Pytorch, bitbucket, Docker, MlFlow
    - worked with docker, go, Kubernetes
  • MINES ParisTech
    Research Intern in Deep Learning (Image & Modelisation)
    TECH
    February 2021 - May 2021 (3 months)
    Anomaly Detection using Unsupervised Deep Learning (development made with Keras and Tensorflow)
  • Prophesee
    Machine Learning and Computer Vision Intern
    MECHANICAL ENGINEERING
    May 2021 - August 2021 (3 months)
    Ville de Paris, Île-de-France, France
    Worked on machine learning algorithms for event-based applications

    -Review of state of the art & evaluation metrics
    -Design and implementation of algorithms and machine learning methods (Pytorch),
    -Acquisition and cleaning of experimental datasets,
    -Evaluation of the developed approaches.

    Topics covered: Denoising (checkerboard artifacts), Alignment of Frame and Event Based Data, Disparity Estimation and Optical Flow computations.

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Education

  • Master 2 (M2 - Master of Science), Data Science and Machine Learning (DAC/M2A)
    Sorbonne Paris
    2022
    Data Science and Mathematics Master, the master includes courses about: - Apprentissage Statistique - Advanced Machine Learning (Language model, NLP, LSTM and GRU, Transformers, Attention Module, CNN...) - Deep Learning for Image Analysis (Sift/BOW, Convolutions, Deep CNN, image detection, image segmentation, Transformers for Vision, Transfer Learning, AutoEncoders, Gans) - Reinforcement learning (Markov, TD(n), DQN, Actor Critic, PPO, TRPO, Meta Learning, Curriculum Learning...) - Machine Learning (Bayesian Machine Learning, SVM, Neural Process, Gaussian Process...) - Research in data science and Methodology - Large Scale Database
  • Master In Science and Executive Engineering - Ingénieur Civil Programme Grande Ecole
    MINES ParisTech
    Machine and deep learning, computer vision, data science, app and web development, Stochastic Process, statistics, big data, information system, mechanics, Automatics.

Skill set

Categories