Embedded AI Engineer Intern

Greenerwave; Paris; Presencial; EUR 10.000 - 15.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Lunch subsidy

CSE benefits

Paris offices (2nd arrondissement)

Monthly team events

Discussions with technical teams

Multicultural environment

Mentor guidance

Descripción de la vacante

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.

Formación

• Final year of engineering degree or master’s programme, specialising in embedded systems, computer science or electronics.
• Strong interest in machine learning applied to embedded systems.
• Proficient in C++ and Python, comfortable in Linux.
• Familiar with PyTorch or TensorFlow; knowledge of cross-compilation and Yocto is a plus.

Responsabilidades

• Familiarise yourself with two hardware platforms and run an initial neural network on each.
• Develop a common C++ interface to run models on different AI accelerators.
• Set up tests to compare speed, energy use and accuracy across platforms.
• Analyse results to identify capabilities and limitations.
• Integrate models and run them on the embedded platform; adapt models to hardware constraints.
• Measure impact on accuracy and demonstrate on the target platform.
• Document development work and provide usage examples; present results.

Conocimientos

C++

Python

Linux

English communication

Problem solving

Team collaboration

Hardware acceleration awareness

Educación

Final year of engineering degree or master’s program

Herramientas

PyTorch

TensorFlow

ONNX Runtime

Yocto

Descripción del empleo

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.