Nov 2024 – Jul 2025 · 8 mos

• The Agence agileAI is division of the agileDSS Group. As a Director of Applied AI, I'm responsible for leading and executing AI strategies within an organization, translating theoretical AI concepts into practical, impactful solutions. This involves building and mentoring AI teams, identifying and evaluating AI opportunities, and ensuring successful deployment of AI systems to achieve business goals.
• Strategic Leadership & Vision:
• Formulating and executing AI strategies
• Identifying and evaluating AI opportunities
• Architecture, developing and deploying AI solutions
• Building and mentoring AI teams
• Driving AI adoption
• Representing AI to stakeholders
• AI R&D reports for government grants, funding, and tax credit programs
• Technical Expertise & Implementation:
• Staying up-to-date on AI trends
• Hands-on experience with AI models
• Ensuring quality and performance
• Managing complex projects
• Collaboration & Communication:
• Partnering with business teams
• Working with external vendors and partners
• Communicating effectively (presenting complex technical information to both technical and non-technical audiences, including executives and board members)
• Championing responsible AI
• AI public speaker and writer

Mar 2023 – Nov 2024 · 1 yr 8 mos

Aug 2023 – Nov 2024 · 1 yr 3 mos · Montreal, Quebec, Canada · Hybrid

• AI Strategy:
• Advised executives on AI adoption strategy, assessed organizational AI maturity, and proposed improvements. Delivered generative AI literacy training for leadership and technical staff. Provided updates on AI advancements and facilitated meetings with vendors (Databricks, Gartner) to guide cost-quality-security evaluations for AI solutions.
• Literacy:
• Focused on GenAI training for executives and technical teams to enhance understanding and practical application.
• Upskilling Architects:
• Developed training materials and best practices for deploying AI projects in production, including architectural guidelines and documentation.
• Upskilling Business and IT Personnel:
• Advanced prompt engineering training, methods to evaluate AI systems, and state-of-the-art testing strategies/metrics for GenAI.
• Generative AI Document Research Project:
• Designed solution architecture, resource estimates, and provided end-to-end support for deploying a generative AI tool for document research.
• Responsible AI:
• Analyzed global regulations and scientific advancements in ethical AI. Collaborated with legal teams to align principles with Canadian/Quebec laws for AI use in finance.
• Databricks Reproducibility Project:
• Addressed the financial sector’s 10-year reproducibility requirement by proposing Apache Spark-based architectures. Compared cloud vs. on-premises deployments, Spark modes (isolated/YARN/Kubernetes), and VM vs. container solutions.
• Personal Assistant Initiative:
• Evaluated AI-based assistants, highlighting scientific/technical limitations and risks. Published a report on programming assistant technologies and provided recommendations.
• MLOps Project with Databricks:
• Collaborated with Databricks to clarify requirements and review proposals for operationalizing machine learning workflows.
• AI Technology Selection Initiative:
• Identified internal AI use cases, defined required AI tasks, and shared best practices for technology selection and implementation.

Jun 2023 – Oct 2023 · 4 mos · Quebec, Canada · Remote

Apr 2023 – Jul 2023 · 3 mos · Montreal, Quebec, Canada · Remote

Jun 2021 – Dec 2022 · 1 yr 6 mos · Montreal, Quebec, Canada · Hybrid

• I'd a team of around 12 members, including applied ML researchers and AI developers (data and ML engineers) into one team.
• Defined a new deterministic process for researchers
• Defined training and skills development to reach career plan targets for the team
• Motivate, coach, guide the applied Machine Learning experts and AI developers
• Guide research activities and validate results
• Work with CPO (Chief Product Officer) to gather product requirements, define research priorities and to share progress status
• Share progress status with the Sr. VP of Engineering and provide support for process enhancement
• Act as a product owner for features that are related to machine learning
• Presentations to AI strategy, Marketing teams and brainstorming
• Support solution team into tackling customer’s use cases
• Support for preparing proposals
• Claim investment tax credit for Scientific Research and Experimental Development (SR&ED) reports

Oct 2020 – Feb 2021 · 4 mos · Montreal, Quebec, Canada

• After submitting an RFP, a large financial institution has selected our proposal.
• The goal of this project is to build an MLOps platform based on Azure ML, Azure DevOps, Azure Kubernetes Service (AKS), Azure Blobs, Databricks, Python, Terraform
• MLOps solution architecture based on Azure MLOPs reference architecture
• Implementation of MLOps workflows
• Migration of 2 existing machine learning models (batch and real-time) from on premise into the MLOps platform
• Managing tasks, coach and support other consultants
• Recommendations for MLOps best practices and security
• Provided MLOps training session for the executive and business analysts
• Workshop sessions with hands-on exercises for customer's technical staff
• Knowledge transfer to customer’s architect, machine learning engineer, data engineer and Azure specialist

Sep 2020 – Oct 2020 · 1 mo · Montreal, Quebec, Canada

• A large financial institution wanted to build an MLOps platform hosted in Azure Cloud.
• Executive meetings with the customer
• Preparing an RFP reponse for this opportunity

Nov 2019 – Jul 2020 · 8 mos · Montreal, Quebec, Canada · Remote

• Migration of analytic from Netezza and SAS into Hadoop, Hive and Spark based platform
• Leading a team of 5 Data Engineers, 3 QA testers and 2 Tableau developers

Oct 2019 – Jun 2021 · 1 yr 8 mos · Montreal, Quebec, Canada · Hybrid

• Tripled the size of data scientists and data engineers
• Defined training and skills development to achieve for each member of the team
• My motivated team had successfully over-passed other teams of ratio in training and professional certifications
• Presented service offering to IBM business development partners
• Helping for preparing proposals (RFP and RFI)
• Working on various projects with customers
• Analyzed data of IBM’s Think 2020 conference for the executive
• Participating as presenter into IBM internal AI events
• Representing IBM into various events

Jul 2019 – Oct 2019 · 3 mos

• Artificial intelligence R&D project in the field of self-checkout in retail stores
• Computer vision

Apr 2019 – Jun 2019 · 2 mos

• Optimizing warehouse management
• Designing and presenting high level solution to customer
• Analyzed customer data

Jan 2019 – Mar 2019 · 2 mos

• The goal of the project is to use Artificial Intelligence for extracting insights from the Wall Street Journal articles and headlines to help traders
• Pipeline for extracting data from World Street Journal web service, parsing JSON messages and aggregation of data
• Pipeline for training sentiment analysis models, testing and selecting models
• Production pipeline for extracting data from the World Street Journal and inferring sentiment analysis model to score sentiment of articles
• Named entity extraction
• Deployment of the inference pipeline in AWS using a Lambda architecture
• Mentor team of data and machine learning engineers
• White paper
• Mentor team of data and machine learning engineers
• Received award for leadership and knowledge sharing

Nov 2018 – Jan 2019 · 2 mos

• Using artificial intelligence for Smart City Security risk reduction.
• Brainstormed with domain and data experts
• Defined classes of Machine Learning challenges to solve and prioritize them
• Summarized project phases and provided estimates
• Defined relevant features to extract from raw data
• High level architecture design
• Transferred knowledge to a Data Scientist and mentoring

Oct 2018 – Oct 2019 · 1 yr

• As an artificial intelligence and data science SME prime:
• Supporting CGI for finding artificial intelligence business opportunities
• Helping in defining a strategy for artificial intelligence projects
• Provide support for proposals
• Mentoring and training data scientists and engineers
• Tech talks
• Developing artificial intelligence prototypes and demos to show internally and to customers
• Meeting with executive customers
• AI SME prime and technology adviser for Scale.ai, the AI-Powered Supply Chains Supercluster

Oct 2016 – Oct 2018 · 2 yrs

• Olameter Inc. wanted to hire an experienced professional Data Scientist having a strong experience in software engineering. I was the first data scientist that Olameter Inc. has hired.
• After a 4 months, my research work allowed me to build an MVP and customers were interested. 2 months later, I deployed the 1st version of the AI solution into production running in Dockers. This work has allowed Olameter Inc. to win more than 10 millions $ in contacts
• I was promoted for a role of Director of AI R&D and started building my team.

Oct 2016 – Mar 2018 · 1 yr 5 mos

• Leading large scale computer vision projects
• Image processing, image segmentation, object detection (R-CNN), classification, deep learning (CNN)
• Experimental and production data processing pipelines
• Ubuntu, Git, Docker, Python, Jupyter, OpenCV, Keras, TensorFlow, Theano, NVIDIA multi-GPU server

Mar 2014 – Oct 2016 · 2 yrs 7 mos · Montreal, Canada Area

• Anomaly detection, classification, regressions, Bayesian networks and time series
• High performance computing: MPI, Grid Engine
• Cloud computing with Amazon Web Services
• Big data: Hadoop/MapReduce and Spark/MLlib & ML

Nov 2012 – Mar 2014 · 1 yr 4 mos · Montreal, Canada Area

• - Voice to text R&D

Mar 2007 – Nov 2012 · 5 yrs 8 mos · Dorval, Quebec, Canada

• Development of air traffic management functionalities for ATOP (Air Traffic Management) product in collaboration with Lockheed Martin.
• Aeronautical protocols parser based on context-free grammars and finite-state machines
• Converting air traffic simulation scenarios using recursive tree spanning algorithms and language parsing techniques. This work has saved months of work for the testing team
• Configurable automatic installation of the Air Traffic Management system on Unix servers.
• Participated in FedEx day competition. My prototype solution became later a product functionality
• Enhancing engineering procedures
• Providing onsite support to the Federal Aviation Agency (Government of the USA) and Lockheed Martin customers.

Mar 2001 – May 2002 · 1 yr 2 mos · Brossard

• Air Traffic Control Simulation
• Successfully delivered 3 air traffic control simulation towers to Nav Canada, a project of 4 million $. I was responsible of the planning, documentation and installation. The success of the project was announced in Canadian news.
• Worked on project for NASA, US Air Force and Nav Canada

Oct 2001 – Feb 2007 · 5 yrs 4 mos · Montreal, Canada Area

• Anomaly detector that continuously learns/updates models and detects anomalies from a continuous stream of 92,000 variables (big data)
• Using an in-memory database for storing compressed data of few days for better performance
• SNMP protocol client for sending detected alarms to another monitoring system using SNMP traps
• User graphical interface to connect to the anomaly detector for analyzing root cause of alarms and visualizing real-time traffic of data
• AIRCOM data link Network and Services Management based on TMN/FCAPS model
• Development and integration of web-based statistical reports into a portal

Apr 1999 – Mar 2001 · 1 yr 11 mos · Saint-Laurent, Quebec, Canada

• - Network Management projects

Jan 1999 – Aug 2008 · 9 yrs 7 mos · Montreal, Canada Area

• Contracts with Standard Life, Nortel Networks and Adacel Inc.
• Large scale software development projects for insurance, telecommunications, air traffic simulation and air traffic management.
• Anomaly detection applied to a stream of big data using online learning strategy
• Network infrastructure and services management applications using TMN/FCAPS model
• Business intelligence reports and dashboards
• Parallel and distributed systems
• Servers installation and network configuration
• Software build, packaging and installation in clusters

Jan 1999 – Mar 1999 · 2 mos · Montreal, Canada Area

• Design and Development of an interface between the Corporate Cash Disbursement System and the SLX (Fund Manager System)
• Reporting

Jun 1998 – Dec 1998 · 6 mos · Montreal, Canada Area

• Collaborate with Kenan Systems (MIT start-up) for modeling multi-services billing functionality
• Mediation between VoIP switch and billing system (Bell Core AMA records)
• Reporting for Finance, Marketing and Sales business units

Feb 1998 – May 1998 · 3 mos · Montreal, Canada Area

• Application and Data migration from Mainframe into IBM RS6000 / Sybase
• Reporting

Jun 1997 – Jan 1998 · 7 mos · Montreal, Canada Area

• - Analysis and Development of new functionalities for an Integrated Information System dedicated for the Traveling Industry

Aug 1993 – Aug 1996 · 3 yrs · Bois d'Arcy, Saint-Quentin-en-Yvelines, France

• State-of-the-art study on word spotting.
• R&D on connected word recognition algorithms.
• Pattern recognition algorithms.
• Language modeling.

Apr 1993 – Sep 1993 · 5 mos · Orsay, France

• State-of-the-art study on Statistical Language Modeling
• Class based n-gram models optimization
• Study of smoothing methods