Deep Learning Research Engineer

Resumen del puesto
Indefinido
Boulogne-Billancourt
Unos días en casa
Salario: 60K a 80K €
Fecha de inicio: 31 de agosto de 2025
Experiencia: > 3 años
Formación: Licenciatura / Máster
Competencias y conocimientos
TensorFlow
Pandas
C++
Scipy
Python
+3

digeiz.
digeiz.

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El puesto

Descripción del puesto

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.


Requisitos

Qualifications

  • Master’s in deep learning, computer vision, machine learning, or equivalent experience (or PhD, even better).

  • At least 3 years of professional experience with machine learning algorithms and tools (Ph.D. considered equivalent to professional experience after master).

Skills

  • 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.

Values

  • Team-player willing to build a leading company

  • Reliable, gets things done

  • Ambitious


Proceso de selección

  • Phone call with CTO

  • Technical test

  • Lunch with R&D team

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