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Deep Learning Acceleration – Embedded Engineer

Tel Aviv, Israel Engineering

Job Description:

We are looking for an applied deep learning engineer, with an emphasis on accelerating models inference on an embedded device.


  • Accelerating DL models to run efficiently over our embedded device. It includes benchmarking for efficient models, implementing/optimizing specific NN layers (from scratch in C++/Cuda).
  • Converting DL models.
  • As part of the DL team, you will also work on the full development cycle of applied deep learning problems such as object-detection, fine-grained classification, change detection. This includes, research, implementation and deployment to the edge device.


  • 4+ years of experience in algorithm development and performance-tuning/optimizations , or equivalent academic background.
  • Hands-on experience in accelerating inference of deep learning models.
  • Hands-on experience in TensorRT is advantage.
  • Excellent coding skills in C/C++.
  • Knowledge in python and Cuda are an advantage.
  • Expert knowledge of at least one DL framework , such as TensorFlow / PyTorch / MXNet.
  • Experience using GPU-accelerated libraries (e.g. cuDNN and cuBLAS).
  • Ability to work collaboratively in a team environment and to communicate complex ideas effectively.

If you’re excited by what we’re doing and want to be part of our journey,
email us at

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