Master's in Sciences + 5 years' or PH.D. + 2 years' practical experience in an Engineering field related to machine learning, deep learning, computer vision, or data science.
Practical experience in most of the following areas is required:
- feature extraction and algorithm development using optical and thermal data sources
- deep learning, CNN, semantic segmentation, object classification
- deep learning frameworks, such as Tensor Flow, Keras, PyTorch, NVIDIA Deep Stream
- classic machine learning approaches such as SVM, LDA, PCA, Na√Øve Bayes, k-Means, etc.
- image processing, machine vision approaches
The candidate will have the opportunity to work on applied solutions where Artificial Intelligence (AI) is embedded into products to increase their performance.
The candidate will have access to a diversity of datasets, tools and frameworks required to develop algorithms and deep neural networks.
The candidate will be part of a team developing end to end AI solutions to be embedded into high performance vision sensors (synthetic image generation, image processing, deep neural network research and development, features extraction and algorithm development, inference acceleration on hardware platforms, system performances optimization and support).