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I have deployed or helped deployed at least 7 AI services to production, including deep learning and machine learning services. Publications (580+ citations): https://scholar.google.com/citations?user=RzL_a1gAAAAJ&hl=en GitHub profile (8000+ stars): https://github.com/guillaume-chevalier/ I'm an enthusiastic, audacious and innovative Machine Learning Expert with over 13+ years of coding experience, specializing in NLP, Generative AI, and Deep Learning. A bit more than a decade ago, I committed to specializing in AI. - Consistently recognized as a high achiever in R\&D projects, coding competitions, and hackathons. - Founded Neuraxio Inc., delivered cutting-edge machine learning services to numerous companies. - Fueled by a vibrant creative energy, I deliver my best work on complex, open-ended challenges, thriving in high-trust environments that grant full ownership from exploration to execution. - My leadership style mirrors this: I provide the strategic vision and empower my team with the creative autonomy needed to pioneer new solutions and deliver impactful results. Combining analytical rigor with a creative and open-minded approach, I thrive on delivering results and nailing requirements, often going above and beyond.
Linköping University
International (Bilateral) Profile (a.k.a. Bachelor exchange studies), CSE
September 1, 2016 – January 1, 2017
Université Laval
Bachelor’s Degree, Software Engineering
September 1, 2015 – May 1, 2019
Cégep de Sainte-Foy
Natural Sciences, with additional classes picked in: Mathematics and Computer Science
September 1, 2012 – June 1, 2015
Les Compagnons-de-Cartier
High School, Information Technology
September 1, 2007 – May 1, 2012
helloDarwin
Senior Software Developer
April 1, 2025 – May 1, 2026
Montreal, QC · Hybrid
Secureworks
Software Senior Principal Developer
December 1, 2022 – December 1, 2024
Montreal, Quebec, Canada · Remote
Neuraxio Inc.
Machine Learning Director
May 1, 2018 – November 1, 2022
Capitale-Nationale, Quebec, Canada
Vooban
Deep Learning, R&D
May 1, 2017 – October 1, 2017
Quebec, Canada
Stamford Scientific International, Inc. (SSI Aeration)
Deep Learning, R&D
September 1, 2016 – March 1, 2017
Remote, U.S., from Sweden & Canada
InnovMetric Software
C++ Developer, R&D
May 1, 2016 – August 1, 2016
Quebec, Canada
Université Laval
Teacher Assistant
March 1, 2016 – April 1, 2016
Quebec, Canada
Bentley Systems
3D visualization prototypes, Applied Research
June 1, 2015 – August 1, 2015
Quebec, Canada
Coveo
Cloud Specialist, R&D
May 1, 2014 – August 1, 2014
Capitale-Nationale, Quebec, Canada
Les Consultants Horticoles Inc.
Webmaster & CAD Drafter
July 1, 2012 – April 1, 2014
Saint-Augustin-de-Desmaures
How-to-Grow-Neat-Software-Architecture-out-of-Jupyter-Notebooks
October 13, 2018 – November 6, 2022
Growing the code out of your notebooks - the right way.
View ProjectMultilingual-Latent-Dirichlet-Allocation-LDA
September 3, 2018 – July 16, 2024
A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.
View ProjectSpiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
August 16, 2018 – November 6, 2022
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
View ProjectLinear-Attention-Recurrent-Neural-Network
May 3, 2018 – August 20, 2018
A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)
View ProjectGloVe-as-a-TensorFlow-Embedding-Layer
March 6, 2018 – October 13, 2018
Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.
View ProjectHyperopt-Keras-CNN-CIFAR-100
May 27, 2017 – May 6, 2018
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
View Projectseq2seq-signal-prediction
March 31, 2017 – March 25, 2023
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
View ProjectAwesome-Deep-Learning-Resources
November 27, 2016 – January 18, 2024
Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier
View ProjectHAR-stacked-residual-bidir-LSTMs
November 26, 2016 – November 6, 2022
Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.
View ProjectLSTM-Human-Activity-Recognition
May 18, 2016 – November 6, 2022
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
View ProjectSequence Models
Coursera
June 24, 2026 – Present
Helm for Beginners
KodeKloud
June 24, 2026 – Present
The OWASP API Security Top 10: An Overview
June 24, 2026 – Present
Containerized Applications on AWS
Coursera
June 24, 2026 – Present
Neuraxio AI Programmer
Neuraxio Inc.
June 24, 2026 – Present
Licensing & Artificial Intelligence
ROBIC
June 24, 2026 – Present
E-Marketing and E-Commerce Strategies
École des dirigeantes et dirigeants HEC Montréal
June 24, 2026 – Present
Discovering Personality
Jordan B. Peterson
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Big Data with PySpark
DataCamp
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential (with Honors)
Coursera
June 24, 2026 – Present
Learning How to Learn: Powerful mental tools to help you master tough subjects
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Machine Learning (Matlab / Octave)
Coursera
June 24, 2026 – Present
Kubernetes Certified Application Developer (CKAD) with Tests
Udemy
June 24, 2026 – Present
AI Training - Generative AI with Grant Thornton
Raymond Chabot Grant Thornton
June 24, 2026 – Present
Certified Kubernetes Application Developer (CKAD)
The Linux Foundation
June 24, 2026 – Present
Datadog: Performance monitoring tool (from Zero to Hero)
Udemy
June 24, 2026 – Present
The Complete Hands-On Introduction to Apache Airflow
Udemy
June 24, 2026 – Present
Building Recommendation Engines with PySpark
DataCamp
June 24, 2026 – Present
Machine Learning with PySpark
DataCamp
June 24, 2026 – Present
Feature Engineering with PySpark
DataCamp
June 24, 2026 – Present
Cleaning Data with PySpark
DataCamp
June 24, 2026 – Present
Certified Kubernetes Administrator (CKA)
The Linux Foundation
June 24, 2026 – Present
Udemy Labs - Certified Kubernetes Application Developer
KodeKloud
June 24, 2026 – Present
Kubernetes for the Absolute Beginners - Hands-on Tutorial
KodeKloud
June 24, 2026 – Present
Docker Training Course for the Absolute Beginner
KodeKloud
June 24, 2026 – Present
Terraform for the Absolute Beginners
Udemy
June 24, 2026 – Present
Concurrency in Go (Golang)
Udemy
June 24, 2026 – Present
Udemy Labs: GoLang
KodeKloud
June 24, 2026 – Present
LangChain - Develop LLM powered applications with LangChain
Udemy
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from academic research reproductions to real-world product deployments, indicates a strong drive for continuous learning and practical application. Their entrepreneurial background and involvement in hackathons suggest an innovative and results-oriented mindset. The breadth of skills and technologies listed, combined with experience in various company sizes (startup to large enterprise), suggests adaptability and a willingness to engage with different technical and business challenges. The target role of Data Scientist aligns well with their deep learning, machine learning, and AI development experience.
Soft Skills & Operational Fit
The candidate's experience at Neuraxio Inc. as Machine Learning Director and at Secureworks as Software Senior Principal Developer highlights strong communication, teamwork, and leadership skills. They have experience synchronizing cross-functional teams, interacting with stakeholders, and mentoring. The descriptions also suggest a proactive attitude, problem-solving capabilities, and the ability to deliver under pressure, as seen in hackathon successes and project ownership.