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Director of AI/Machine Learning
I am interested in applied research in artificial intelligence, from theory to practice. Strong from a decade of experience in Machine Learning, I excel at taking an idea or a business opportunity, breaking it down, finding the underlying need, and solving it. With critical thinking and an open mind, I question the status quo and constantly look for ways to improve things (myself included). I contribute well to a multidisciplinary team and can lead it by providing a solid set of skills ranging from foundational math to software engineering. I love to learn from more knowledgeable people while fostering young talents into independent and capable teammates. As I write my prose in Python, Machine Learning frameworks such as Scikit-Learn and PyTorch have become second nature. I focus on writing reusable high-quality code, easily going from whiteboard designs to near production-ready proof of concepts. In the last few years, I applied deep learning primarily to Natural Language Processing while keeping an eye on the rest of the field. My current interests extend in both directions, theory and application, by keeping up-to-date with the current literature and looking for opportunities to apply it. This section is for you LinkedIn Bot, keyword galore: Deep Learning, Representation Learning, Neural Networks, ANN, CNN, RNN, Transformers, BERT, ELMo, NLP, NLU, Python, Pytorch, pandas, matplotlib, numpy, scipy, linux, bash, visualization, graph, graph neural network, GNN, database, SQL, Azure, multidisciplinary team, SVC, k-means, knn, supervised learning, unsupervised learning, semi-supervised learning, clustering, classification, regression, leadership, creative thinking and many more.
Udacity
AI-Powered Software Engineering Nanodegree
January 1, 2026 – January 1, 2026
Université de Montréal
Maîtrise informatique, Intelligence artificielle
January 1, 2018 – January 1, 2021
Udacity
Deep Learning Nanodegree Foundation, Deep Learning
January 1, 2017 – January 1, 2017
Udacity
Machine Learning Engineering Nanodegree, Machine Learning
January 1, 2015 – January 1, 2016
Coursera
Statement of Accomplishment, Data Science
January 1, 2013 – January 1, 2013
UQAM | Université du Québec à Montréal
Certificat, Informatique et développement de logiciel
January 1, 2010 – January 1, 2013
Université de Montréal
DESS, Pédagogie
January 1, 2008 – January 1, 2009
Université de Montréal
Bac, Mathématiques
January 1, 2004 – January 1, 2007
Explorance
Director of AI/ML
January 1, 2020 – Present
Montréal, Québec, Canada
Explorance
Machine Learning Engineer - Python Sorcerer Supreme
May 1, 2018 – January 1, 2020
Montréal, Québec, Canada
Alpha Tau
Machine Learning Connoisseur - Python Sorcerer
June 1, 2016 – December 1, 2020
Datacratic
Data Geek :: Machine Learning Specialist :: Mathe-magician :: Cosmic Hacker
January 1, 2014 – June 1, 2016
Montréal
SAP
Software Engineering - Data Scientist
July 1, 2012 – September 1, 2013
Montréal
Alpha Tau
Travailleur autonome
January 1, 2012 – July 1, 2012
Boucherville
UQAM
Correcteur
September 1, 2011 – January 1, 2012
Montréal
Morneau Shepell
Actuaire analyste | Implantation de régimes de retraite
May 1, 2006 – September 1, 2011
Région de Montréal, Canada
Fuzzy Adventure
October 1, 2012 – Present
Fuzzy Adventure est un projet excessivement stimulant sous le chapeau d'intelligence artificielle. Nous utilisons différentes technologies d'apprentissage machine et de traitement naturel du langage afin de fournir un service facile d'utilisation pour le Business Intelligence. Les utilisateurs pourront poser une question au système et celui-ci fera en sorte de fournir une réponse significative. Fuzzy Adventure is a very exciting artificial intelligence project. We use different machine learning and NLP technologies to provide easy-to-use Business Intelligence. The user will ask questions to the system and get a significant answer.
Maîtrise de l'italien sur Duolingo : Intermédiaire (estimation)
Duolingo
June 24, 2026 – Present
Maîtrise de l'italien sur Duolingo : Élémentaire (estimation)
Duolingo
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across various companies (Explorance, Alpha Tau, Datacratic, SAP) and roles, from individual contributor to Director of AI/ML, suggests adaptability. Their involvement in both personal and professional AI projects, including open-source contributions, indicates a passion for the field. The educational background is extensive and highly relevant to AI/ML. However, the project descriptions are limited in terms of team collaboration details or specific cultural contributions, making a comprehensive cultural fit assessment challenging. The target role is AI Engineer, and the candidate's experience is highly aligned, but the lack of specific cultural data from the assessment limits a deeper analysis.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and 'player-coach' capabilities, indicating a blend of technical depth and team development skills. Their experience in driving 'AI-first' transformations and making strategic technical decisions (e.g., migrating inference infrastructure, deliberately withdrawing models due to bias) suggests a proactive, responsible, and business-oriented approach. The descriptions also highlight problem-solving, innovation, and adaptability. However, the psychometric test score is 0, which means there is no data to evaluate logical reasoning, work attitude, stress handling, and team collaboration. This is a significant gap in assessing operational fit.