About François
Engineering leader with a proven track record in designing, building, and delivering mission-critical systems. Steers multidisciplinary teams to develop & deploy software, data, and AI products in quick iteration with end users and stakeholders - shipping in weeks, not years. Fosters a culture of ownership for deployed solutions, ensuring that end users derive maximum value from our services. Actively travels to build, integrate, test, and deploy in real-world settings as needed.
Graduated from École Centrale de Nantes with a Master of Science in Statistics & Signal Processing, I developed a deep understanding of data science, engineering, and how computers and networks work with practical applications in complex environments - from cloud to edge.
A trained communicator, I break down complex technical topics to diverse audiences up to C suites and senior military leaders with clarity and confidence to ensure alignment with the vision. Attached to maintain a high level of proficiency in my field, I also give courses on AI/ML in leading French universities.
Building on my engineering background, I cultivate my financial literacy to develop solid fundamentals for my entrepreneurial ventures. Successfully passing the Autorité des Marchés Financier exam - French financial authority - equipped me with a deep understanding of investment and market dynamics to navigate the complex regulatory landscapes in the Eurozone. This financial acumen ensures that each decision is both informed and strategically sound in driving an entrepreneurial roadmap.
French
Native or bilingual
English
Native or bilingual
German
Conversational
Remote only
Primarily works remotely
Experience
- Schneider ElectricMachine Learning EngineerENERGY AND UTILITIESMarch 2019 - September 2020 (1 year and 6 months)Greater Boston AreaDesigned a high-throughput and highly-available ETL pipeline to process IoT data. Pioneered Schneider's Machine Learning Platform to scale and automate analytics deployment.- Designed a real-time ingestion pipeline for IoT data, based on the Hadoop ecosystem.- Increased pipeline maintainability and engineer productivity by modeling the ingest pipeline as a finite state machine. Monitored critical state transition with messages collected on Azure Service Bus, giving visibility to SREs to ensure processing-time SLA compliance.- Reduce analytics component deployment by implementing a Machine Learning framework to automate data preparation and manage ML models' lifecycle.Leveraged knowledge in domain and data modeling, Python 3.7, Microsoft Azure (especially its messaging product Azure Service Bus), Hadoop ecosystem for big data processing (especially Apache NiFi and Kafka)
- KplerData EngineerENERGY AND UTILITIESApril 2018 - January 2019 (9 months)Paris, FranceParticipated in the development of a new commodity tracking platform and revamped the core algorithm for cargo allocation by implementing a graph theory approach.- Provided our users with exclusive energy market insights by scaling up the ETL pipeline using Python and PostgreSQL to handle an additional source of data.- Cut down core service runtime by 70% using graph theory. Pitched critical stakeholders over the benefits of a graph resolution strategy and thoroughly documented the new approach.- Enhanced engineers' productivity on the core service by writing exhaustive test cases using the pytest framework and executed by our CI/CD tool.Leveraged knowledge in Python 3.7 programming (especially the networkx and pytest library), AWS (EC2 instances and spot market), PostgreSQL, and version controlling with Git.
- RapLyrics.euCo-founder, technicalCULTUREJanuary 2018 - September 2018 (9 months)Nantes, FranceEnvisioned and brought life to a text-generative web app using convolutional neural networks to conceive original rap music lyrics. https://raplyrics.eu/- Implemented an ETL in python to build a high-quality corpus of songs used to train the lyrics generation model.- Built and trained a word-to-word generation model using TensorFlow. Contributed back to the open-source by releasing source-code and sharing the architecture in a blog post.- Constructed the most cost-effective architecture to serve the model by running a benchmark using a Go proxy server. Saved 90% of monthly bill by shifting from a bare AWS VM to a Google Cloud Run service.
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Education
- Master of Science - MSEcole centrale de Nantes2018- Machine learning and AI - Supervised and unsupervised methods. Neural Networks - CNN, LSTM - SVMs, Decision trees. - Image Analysis and Processing - Frequency and Spatial Filtering, Morphological Image Processing, Deconvolution. - Master Thesis: Cancer cell-detection in PET scans, in partnership with Nantes’ University Hospital Oncology department. Python programming and Jupyter notebooks for dynamic visual interpretation of image processing results. - Entrepreneurship - Ideation, Pitching, Business Plan redaction, Searching funds, Conducting Market Surveys.
- Bachelor of Science - BSPrytanée National Militaire de La Flèche2015Two-year of intensive preparation courses for the entrance exams to top French Engineering schools. - Major in physics and chemistry. - Minor in mathematics and python programming. Linear Algebra, Statistics, Python Programming, Algorithms, and Data Structures. Top 1%
Certifications
- Structuring Machine Learning Projectsdeeplearning.ai2019
- Neural Networks and Deep Learningdeeplearning.ai2019