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Greenerwave is offering an internship that blends AI with embedded antenna systems. You will implement neural networks on embedded hardware, build a shared C++ interface for accelerators, and benchmark performance and power across platforms. Collaboration across software and modelling teams is key.
You will bridge AI and hardware constraints under guidance, documenting workflows and delivering a demo on the target platform for a hands-on learning experience in a cutting-edge field.
We want to explore the integration of neural networks directly into our antenna systems. Our aim is to integrate our models so that they run efficiently in our embedded systems. Working at the interface between the Software and Algorithm & Modelling teams, you will contribute to deployment and compare different hardware acceleration solutions, assessing their performance, power consumption and model accuracy.
Reporting to Louis, Software Engineer, this internship will allow you to bridge artificial intelligence and embedded systems, from creating a common software interface for multiple accelerators to running models on a target platform. You will also learn to adapt a neural network to hardware constraints, in collaboration with the Algorithm & Modelling team.
Interested in joining us? Don’t meet all the criteria?
Above all, we are looking for someone who is motivated, curious and ready to learn, within a team that will support their skills development.
You are in the final year of an engineering degree or master’s programme, specialising in embedded systems, computer science or electronics . You have a strong interest in machine learning and would like to apply it to embedded systems. Your technical skills You have programming skills in C++ and Python , You are comfortable working in a Linux environment, You have a basic understanding of deep learning, using PyTorch or TensorFlow, Some knowledge of cross-compilation, Yocto, TensorFlow Lite, ONNX Runtime, model quantisation or GPU computing would be a plus, Knowledge of radio frequency technology or antennas would also be appreciated, but is not essential, You are comfortable communicating in English, both verbally and in writing.
Your approach to work You enjoy exploring technical documentation to understand and use new tools, You are thorough and approach problems methodically, You are willing to investigate the root cause of a problem and debug a toolchain, You value cross-team discussions to move forward a project at the intersection of software and algorithms.