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Engineering @Evy
My background is in Machine Learning and NLP. I started my career as a data scientist but over the years, I have been focusing more and more on backend and software architecture of ML systems. It has been 3 years + now that I've been designing and maintaining such systems, with a focus on infrastructure, CI/CD and microservices architectures. I am also an enthusiast of software craftsmanship and an ambassador of the software culture. I like to practice pair or mob programming and am a recent TDD practitioner. I recently joined Evy to work on a high load and performance API, built with #Golang, #gRPC and #Kafka among others.
Universite de Lorraine
Master's degree, Fundamental and Applied Mathematics
January 1, 2017 – January 1, 2018
CentraleSupélec
Master of Engineering, Computer Science, Applied Mathematics, Signal Processing, Telecommunications, Electrical Engineering
January 1, 2014 – January 1, 2018
Lycée Gustave Eiffel
Classes Preparatoires for the french "Grandes Ecoles" competitive exams
January 1, 2011 – January 1, 2014
Lycée Gustave Eiffel
Scientific Baccalauréat
January 1, 2008 – January 1, 2011
Evy
Senior Software Development Engineer
June 1, 2022 – Present
Bordeaux, Nouvelle-Aquitaine, France · Remote
BRYTER
Senior Machine Learning Engineer
June 1, 2021 – June 1, 2022
Berlin, Germany · Remote
FORTIA Financial Solutions
Machine Learning Engineer
September 1, 2018 – May 1, 2021
FORTIA Financial Solutions
NLP Research Engineer | Intern
April 1, 2018 – September 1, 2018
Horus Technology
Machine Learning Engineer | Intern
January 1, 2017 – August 1, 2017
Milan, Lombardy, Italy
Inria
Deep Learning and Computer Vision Research Intern
July 1, 2016 – January 1, 2017
Greater Grenoble Metropolitan Area
Clustering of genes expression
December 1, 2017 – Present
Replicates of algea are exposed to different concentrations of a toxic chemical. Then, using DNA ships, the most active genes are identified. Finally, they are clustered using different ML technics (K-means, GMM, spectral clustering, metric learning...).
ASR for Robot control
September 1, 2017 – Present
Extraction of MFCC coefficients, Dynamic Time Warping, Linear Prediction Coefficients. Frameworks: ROS, Python, C++.
DeepGllim
September 1, 2016 – January 1, 2017
Head-pose estimation by deep regression, coupling CNN and Gllim model (Gaussian Locally Linear Mapping, Deleforge et al 2015). Project completed while interning at INRIA Grenoble in Perception team. Resulted in a CVPR 2017 publication.
Connected glove for gesture-based drone flying
September 1, 2015 – June 1, 2016
Development of a wireless glove for the purpose of controlling a drone based on natural hand gestures.
Software development of a Star-tracker
January 1, 2015 – June 1, 2015
Image analysis applied to celestial navigation.
Cultural Fit Analysis
The candidate has a strong background in research and development, with experience in both academic and industry settings. The project diversity, ranging from ASR for robot control to gene expression clustering and gesture-based drone flying, indicates a broad interest in applying ML across different domains. The transition from ML Engineer to Senior Software Development Engineer at Evy, then back to ML Engineer at BRYTER, suggests adaptability but also a potential preference for ML-focused roles, aligning well with the target ML Engineer role. However, the lack of explicit team-based project descriptions or contributions makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's project descriptions and experience suggest a strong problem-solving aptitude and a research-oriented mindset. The publication record indicates a capacity for independent work and contributing to the scientific community. However, without specific psychometric or English test results, it's difficult to assess communication clarity, logical reasoning, work attitude, stress handling, or team collaboration directly from the provided data.