Deep Learning Engineer

Sumár práce
Plný úväzok
Boulogne-Billancourt
Plat: 55K až 70K €
Dátum nástupu: 31. januára 2025
Niekoľko dní doma
skúsenosti: > 3 roky
Vzdelanie: Magisterský stupeň vzdelania
Zručnosti & odborná znalosť
Generovaný obsah
Opencv
Pandas
Tensorflow
Pytorch
Linear
+2

digeiz.
digeiz.

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Pozícia

Popis pracovnej ponuky

We are opening a Deep Learning Engineer position to scale our GDPR-compliant clothing reidentification in the 25 malls across Europe and the one 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 Embedded team.


Preferované skúsenosti

Qualifications

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

  • 2 years of experience with machine learning algorithms and tools (Ph.D. considered equivalent to professional experience).

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


Náborový proces

  • Phone call with CTO

  • Technical test

  • Lunch with R&D team

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