Resume

🔗

ML Ops Engineer

August 2023 - Present

Mistplay, Montreal, Canada 🔗

Machine Learning Engineer

December 2021 - July 2023

Rocket Science Development, Montreal, Canada 🔗
  • Design and implement ML Systems that are scalable, and with varying levels of automation
  • Leverage the ML Ops framework in order to collaborate with our customers to establish solution requirements for the delivery of Machine Learning projects
  • Advise our customers on best practices regarding the implementation of Machine Learning lifecycle using the ML Ops framework
  • Experiment with new technologies and practices that will impact the different steps of an ML project lifecycle
  • Contribute to the R&D process of ML Ops tools that are aimed to be used by MLEs and ML Ops engineers alike
  • Delivered a platform allowing a client to automate their Machine Learning model deployment pipeline, and divided the deployment time by at least 2
  • Lead the development of a Minimaly Viable Product for a Model Monitoring/Performance Management solution
  • Contributed to on-going calls regaridng the status and support of deployed ML applications on a client’s side
  • Participated to the development of an ML Ops professional certificate curriculum

Data Engineering, ML Ops & Machine Learning

July 2021 - November 2021

Desjardins, Montreal, Canada 🔗
  • Coached internal client on the tools ecosystem through workshops in order to empower them in the implementation of their scope of tasks in the applications
  • Lead initiatives required to implement continuous delivery of Machine Learning Models & micro-services
  • Contribute in a significant manner to document and establish an ML Ops practice
  • Manage applications lifecycle within Microsoft Azure AKS (Kubernetes) Environments
  • Collaborate within cross-functional team in order to ensure ML models’ integration with application consuming them

High Performance Computing (HPC) Specialist

March 2019 - February 2021

StragidiAI, Montreal, Canada 🔗
  • Ship a Machine Learning platform components to High Performance Computing (HPC) environments. Support Researchers in the use of a DGX-1 to provide stronger computation capabilities,
  • Provisioning infrastructure as code on AWS to deploy managed solutions (e.g. Elastic Kubernetes Service) critical to the platform workflow,
  • Deploy Hashicorp’s Vault running in Google Kubernetes Engine on Google Cloud Platform, develop CI/CD pipelines by writing modular and maintainable pipeline scripts.

Data science Intern

March 2018 – September 2018

Applied Materials, Santa Clara, California, USA 🔗
  • Worked on the full stack of Machine Learning (ML) and Data Science projects applied to the semiconductor industry;
  • Developed a package running classical ML and Deep Learning for anomaly detection using sensor data for proactive maintenance on critical parts
  • This package also performed computations in the company’s HPC environment inside a Singularity container using Slurm job scheduler

Data Developer

April 2017 - September 2017

Smile Open Source Solutions, Lyon, France 🔗
  • Develop a REST API that exposes queries on a MongoDB database to gather data used for visualization purpose;
  • Migrate the API from R (with OpenCPU) to Python (using Flask) in order to make integration more fluid with the other components of an IoT platform;
  • Conceived Dashboards using R shiny in order to monitor usage of a mobile application destined for truck drivers;
  • Adopt the DevOps approach in order to improve delivery process thanks to tools such as containers (Docker), Version Control (Git), container orchestration (docker-compose, OpenShift), Continuous Integration (CI), Continuation Delivery (CD);

Education 🔗

Master of Computer Science and Data Mining

2016 - 2018

University Lumière-Lyon 2, France,
Machine Learning, Deep Learning, Parallel Computing, Manifold Learning, Mixture Models, Big Data Technologies, Busi-ness Intelligence, Data Mining, Relational Databases, Complexity, Object Oriented Programming, Operations Research.

Bachelor of Decisional Informatics and Statistics

2013 - 2016

University Lumière-Lyon 2, France,
Algorithmic Design, Python Programming, R programming, Calculus, Statistics, Linear Algebra, Inferential Statistics, Relational Database, Operations Research, Microeconomics, Industrial Organizations, Macroeconomics.

Skills 🔗

Machine Learning

Classification, Regression, Mixture Models, Time Series, Unbalanced Learning,Manifold Learning, Bagging, Gradient Boosting

Deep Learning

Single/Multi Layer Perceptron(MLP), Convolutional Neural Networks (CNN), Autoencoders,Long Short Term Memory Networks (LSTM)

Python

Base Libraries, Pandas, Numpy, Scipy, Joblib, Scikitlearn, Flask, Django, Tensorflow,Tensorflow GPU, Pytorch, Keras

R

Base Packages, ggplot2, tidyverse, hadleyverse, caret, e1071, corrplot, MASS, leaflet, rgl,vegan, Shiny, parallel, foreach, parSapply

High Performance Computing (HPC)

Slurm, Singularity, Apex, Horovod

Big Data, BI & ETL

SQL, MongoDB, Cassandra, Hadoop, Spark, Tableau Software, Talend

Other

GNU/Linux, Git, GitLab CI, Docker, Kubernetes, Terraform, Jenkins/Groovy, AWS, GCP, Prometheus, grafana