about 2 hours ago

Machine Learning Engineer (F/M) – Internship Greenerwave

Solutions de connectivité et de détection avec matériaux intelligents.

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Internship

Paris

No remote

1,1K €+ a month

5 years of study

about 2 hours ago

Skills we're looking for

Technical aptitude

Problem-solving skills

Team building

Linux

Git

You'll be part of

124 employees

Metallurgy

Artificial Intelligence / Machine Learning

Electronics / Telecommunications

Average age: 33

Founded in 2015

75%

25%

Revenue: 3,4 Millions € en 2024

Employee turnover: 4

Fondée en 2015 et issue de l’Institut Langevin (CNRS et ESPCI), Greenerwave est une Deeptech développant des solutions disruptives de connectivité et de détection. Notre technologie, unique au monde, s’appuie sur des matériaux intelligents et reconfigurables ainsi que des algorithmes inspirés de la physique. Grâce à notre perspective multiculturelle et notre engagement en faveur d’une recherche fondamentale continue, nous révolutionnons l’utilisation des ondes électromagnétiques pour propulser la connectivité mondiale vers un avenir durable et une disponibilité 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 : Systèmes 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 parallèle de développer nos activités de R&D afin d’étoffer notre offre produits à l’ensemble de nos activités tout en étant à la pointe de l’innovation.

You'll be working on

Why this role is key

The digital twins of our antennas are used to configure our technology to steer electromagnetic waves. These models combine a physical understanding of our antennas with trained parameters. This internship aims to further improve the robustness and reliability of our model training.

Reporting to Steph, Software Engineer, you will investigate the factors that can influence training stability and evaluate different approaches to improving it. Working with our Algorithms and Modelling, Radio Frequency and Software teams, you will learn to connect physical modelling, numerical optimisation and experimental analysis through controlled, reproducible comparisons.

Your responsibilities

Understanding the model and its training process

Understand our physics-based antenna models and how they are trained,
Reproduce a training run and measure the variability in the resulting performance.

Diagnosing and improving stability

Set up monitoring of relevant quantities and automatically detect diverging training runs,
Investigate and implement projection, reparameterisation or penalty methods to enforce model convergence at each optimisation step,
Evaluate the impact of these methods on accuracy and computation time.

Optimising and comparing training runs

Improve stopping criteria, initialisation and the reuse of previously trained models,
Compare several model variants under controlled conditions,
Analyse the model’s physical and numerical mechanisms to investigate their influence on the results,

Documentation and reproducibility

Test the code developed and maintain it under version control,
Document the data and training conditions to ensure reproducibility of the results,
Present the methods investigated and the results obtained in reports supported by quantitative data.

We're looking for

Interested in joining us ?

Don’t 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. 😊

You are currently in your final year at an engineering school (or an equivalent university programme), specialising in applied mathematics, simulation or modelling. You have some initial experience in optimisation or in calibrating models using experimental data, and you are interested in wave physics.

Your technical skills

You have a solid foundation in applied mathematics, particularly linear algebra and constrained optimisation,
You can program in Python and have some initial experience with PyTorch or a similar tool,
Knowledge of electromagnetism would be appreciated,
Familiarity with Git or Linux, or experience with GPU computing, would be an additional asset,
You have a good command of written and spoken English, enabling you to work in an international environment.

Your approach to work

You enjoy working in a team and communicate easily with people from a variety of backgrounds,
You are thorough and approach problems methodically,
You enjoy exploring different approaches and proposing creative solutions to technical problems,
You are curious and take the initiative to move your work forward,
You can work independently while seeking support from the team when needed,
If you use AI tools for coding, you critically assess the code and calculations they produce,
You can write clear, well-structured documents to share your results and document your work.

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.

How we hire

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 Elie, Algorithms & Modelling Team Leader and Steph, 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.