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R&D Engineer - Deep Learning -
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
| Data science/Machine learning: design of deep learning models using TensorFlow for computer vision | Software development: Python, C++, C | Parallel programming (CUDA/OpenMP) and distributed systems (MPI) |
Universität Passau
certification, Data science
January 1, 2016 – January 1, 2016
Université Joseph Fourier (Grenoble I)
Doctor of Philosophy (PhD), Computer Science
January 1, 2008 – January 1, 2013
Linköping University
Master's degree, exchange student (ERASMUS), Sweden, Computer science
January 1, 2006 – January 1, 2007
Université Joseph Fourier (Grenoble I)
Master's degree, Computer science
January 1, 2004 – January 1, 2007
HOMIWOO
r&d machine learning/deep learning
June 1, 2022 – Present
Grenoble, Auvergne-Rhône-Alpes, France
Atos
Artificial Intelligence Engineer
January 1, 2016 – August 1, 2022
Greater Grenoble Metropolitan Area
Bull
R&D HPC engineer
January 1, 2012 – December 1, 2015
Greater Grenoble Metropolitan Area
Grenoble INP - Institut polytechnique de Grenoble
ATER (research and teaching assistant)
September 1, 2011 – January 1, 2012
Greater Grenoble Metropolitan Area
LIG / BULL / CEA
PhD thesis
October 1, 2008 – July 1, 2013
Greater Grenoble Metropolitan Area
CEA - Commissariat à l'énergie atomique et aux énergies alternatives
Internship
January 1, 2008 – January 1, 2008
Greater Grenoble Metropolitan Area
IBM
Internship
March 1, 2007 – September 1, 2007
Greater Nice Metropolitan Area
PRAIRIE Artificial Inteligence Summer School (PAISS)
Inria
June 24, 2026 – Present
Data science
Bull
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Questions stratégiques
France Université Numérique / CNAM
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards R&D, academia, and specialized HPC/AI roles. While highly technical, the experience does not directly align with typical product-oriented backend engineering roles that often involve broader system design, API development, database management, and microservices architectures. The lack of diverse project experience outside of ML/HPC could indicate a narrower focus, potentially requiring significant adaptation to a general backend engineering culture. The target role 'Backend Engineer' is broad, and the candidate's profile is very specialized in ML/HPC, which might not be a direct cultural fit for all backend teams.
Soft Skills & Operational Fit
The candidate's extensive R&D and academic background suggests strong problem-solving, analytical thinking, and independent research capabilities. Experience as a technical leader and teaching assistant indicates potential for mentorship and clear communication of complex ideas. However, the provided data does not offer direct insights into collaboration style, adaptability, or specific operational fit within a typical product-focused backend engineering team.