Solutions de connectivité et de détection avec matériaux intelligents.
FondĂ©e en 2015 et issue de lâInstitut Langevin (CNRS et ESPCI), Greenerwave est une Deeptech dĂ©veloppant des solutions disruptives de connectivitĂ© et de dĂ©tection. Notre technologie, unique au monde, sâappuie sur des matĂ©riaux intelligents et reconfigurables ainsi que des algorithmes inspirĂ©s de la physique. GrĂące Ă notre perspective multiculturelle et notre engagement en faveur dâune recherche fondamentale continue, nous rĂ©volutionnons lâutilisation des ondes Ă©lectromagnĂ©tiques pour propulser la connectivitĂ© mondiale vers un avenir durable et une disponibilitĂ© sans limites.
Nos designs brevetés sont reconnus dans le monde entier par les principaux acteurs industriels et institutionnels au sein des nombreux marchés que nous adressons :
Connectivité : SystÚmes de Communication par Satellites (SATCOM) et Télécommunications (5G, 6G),
Détection : Radar et RFID.
Nos premiers produits SATCOM sont sur le point de voir le jour ! Nous continuons en parallĂšle de dĂ©velopper nos activitĂ©s de R&D afin dâĂ©toffer notre offre produits Ă lâensemble de nos activitĂ©s tout en Ă©tant Ă la pointe de lâinnovation.
Why this role is key
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.
Your responsibilities
Getting started and development
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.
Platform testing and comparison
Set up tests to compare processing speed, energy consumption and model accuracy across the different platforms,
Analyse the results to identify the capabilities and limitations of each solution.
Antenna model deployment
Integrate the models and run them on the embedded platform,
Adapt the models to hardware constraints with support from this team, then measure the impact on their accuracy,
Deliver a demonstration on the target platform.
Documentation and reporting
Document the development work and provide usage examples,
Present the comparison results and the work completed.
Interested in joining us?
Donât meet all the criteria? Apply anyway. Above all, we are looking for someone who is motivated, curious and ready to learn, within a team that will support their skills development. đ
You are in the final year of an engineering degree or masterâs 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.
Reasons to work at Greenerwave
A financial contribution towards your lunches,
Benefits offered by our Social and Economic Committee (CSE),
Offices located in the heart of Paris, in the 2nd arrondissement,
Monthly team events and evenings out to spend time together outside of project work,
Discussions with technical teams to discover the technologies you are working on and better understand their applications,
A multicultural environment bringing together people with varied expertise, where you can learn from others,
Close guidance and support from your internship supervisor to help you progress throughout your internship and prepare to launch your career.
Our recruitment process
Your application is reviewed by the HR team, with no AI-based pre-screening.
An initial 20- to 30-minute phone call to discuss your background, your search and your expectations.
An interview with Louis, Software Engineer, to explore the internship responsibilities in more detail and discuss your technical skills and their practical application.
A final interview with a member of the HR team to get to know you better, discuss your approach to work and answer your questions.
Throughout the process, we keep you informed of the progress of your application and remain available to answer your questions. We provide feedback at every stage, with constructive insights to help you understand our decision.
We welcome applications from people of all backgrounds, regardless of ethnicity, gender, age, sexual orientation, disability or religion. We value diversity and believe that everyone brings a unique perspective that enriches our team.
In short
Founding year
2015
Employees
124
Average age
33
Turnover rate
4
Annual revenue
3,4 Millions ⏠en 2024
Gender
25%
75%