Emploi Tunisie » Offres d'emploi à Tunis » Ingénieur - Computer Vision

Ingénieur - Computer Vision

  • Qubitron
  • Tunis, Tunisie
  • Il'y a 1 mois
Postes vacants:
1 poste ouvert
Type d'emploi désiré :
CDD, Contrat al Karama, SIVP
Experience :
1 à 3 ans
Niveau d'étude :
DESS, DEA, Master, Bac + 5, Grandes Ecoles
Rémunération proposée :
Entre 1500 DT et 2000 DT
Genre :
Indifférent

Description de l'emploi

Job Description:

We are seeking a dynamic and skilled Junior Engineer with a background in Artificial Intelligence, Machine Learning, and Imaging. The ideal candidate will have expertise in Convolutional Neural Network (CNN) structures, training of CNNs, simulated and image generation, image processing, and fast implementations on CPU, GPU, and FPGA.

Responsibilities:

  1. CNN Structures: Design and implement Convolutional Neural Network structures tailored for various applications in the realm of imaging and artificial intelligence.

  2. Training of CNNs: Develop and execute training protocols for CNNs, ensuring optimal performance and accuracy in diverse datasets.

  3. Simulated and Image Generation: Create and utilize simulation environments for generating synthetic data and images to enhance model robustness and performance.

  4. Image Processing: Apply advanced image processing techniques to enhance the quality and relevance of data for training and inference purposes.

  5. Fast Implementations: Implement and optimize algorithms on CPU, GPU, and FPGA for real-time and efficient execution, considering hardware-specific constraints.

 

Exigences de l'emploi

 

 

Qualifications:

  • Bachelor's or Master's degree in Engineering, Computer Science, or a related field.
  • Strong foundation in Artificial Intelligence, Machine Learning, and Imaging.
  • Proficiency in designing and implementing Convolutional Neural Networks.
  • Hands-on experience in training CNNs on diverse datasets.
  • Familiarity with simulated and image generation techniques.
  • Expertise in image processing algorithms.
  • Experience in fast implementations on CPU, GPU, and FPGA platforms.

 

Date d'expiration

10/04/2024