Join our team as a Deep Learning Research Engineer, where you will play a crucial role in scaling our GDPR-compliant outfit reidentification technology across Europe, the US, and the Middle East. You will improve our detection and re-identification models, provide a bibliography on relevant computer vision projects, and facilitate the deployment of R&D prototypes. Candidates should have a Master's or PhD in a related field, at least 2 years of experience with machine learning algorithms and tools, and excellent knowledge in deep learning and computer vision.
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Améliorer nos modèles de détection et de ré-identification en contribuant à l'amélioration de la collecte de données, des architectures de réseaux neuronaux et des paradigmes d'entraînement.
Fournir une bibliographie sur des projets de vision par ordinateur pertinents et mettre en œuvre des prototypes basés sur des articles prometteurs.
Faciliter le déploiement des prototypes de R&D en collaborant étroitement avec les équipes C++ et opérationnelles.
We are opening a Deep Learning Engineer position to scale our GDPR-compliant outfit reidentification in the 25 malls across Europe and the ones coming in the US and Middle East. We are seeking candidates with advanced analytics skills and an academic background in a field linked to applied mathematics, statistics, machine learning, or other related fields. Your missions:
Improve our detection and re-identification models by contributing to enhancing data collection, neural network architectures and training paradigms, pre/post-processing, and performance evaluation.
Provide a bibliography on relevant computer vision projects and implement prototypes based on promising papers.
Facilitate the deployment of R&D prototypes by closely collaborating with the C++ and operational teams.
Master’s in deep learning, computer vision, machine learning, or equivalent experience (or PhD, even better).
At least 2 years of experience with machine learning algorithms and tools (Ph.D. considered equivalent to professional experience after master).
Excellent knowledge in deep learning fields, in particular computer vision, such as object detection, feature extraction and image classification.
Hands-on experience with popular deep learning frameworks (e.g. Pytorch, TensorFlow).
Proficiency with data science and image processing Python libraries (OpenCV, PIL, SciPy, Scikit-Learn, Pandas).
Practical understanding of the mathematics behind modern machine learning, linear algebra, and statistics.
Ability to write high-quality Python code and review code developed by team members.
Team-player willing to build a leading company
Reliable, gets things done
Ambitious
Phone call with CTO
Technical test
Lunch with R&D team
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