Emplois actuels liés à Machine Learning Engineer - Châteaudun, Centre-Val de Loire - Mantu
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Machine Learning Engineer
Il y a 2 mois
Châteaudun (28), France Mantu Temps plein**Who are we? **:Mantu is an independent international consulting player, founded in 2007. Bringing together expert and complementary brands, Mantu stands out for the breadth of its spectrum, responding to all business transformation challenges. Its activities are divided into four practices: Leadership & Advocacy, Technology, Digital Marketing &...
Machine Learning Engineer
Il y a 2 mois
Mantu is a company that thrives on innovation and research and development. Our Mantu Innovation Lab is a hub for staying at the forefront of new technologies and playing an active role in the development and deployment of new services and products tailored to the changing market reality.
By combining our skills with the power of technology, we can support businesses in all their transformation requirements and increase their efficiency. Our mission is to help our customers evolve their markets and find new opportunities for growth, making them aware of the importance of disruptive technologies and helping them make the most of these new tools.
Proposed Internship Topic: Robust Models for Intelligent BuildingsIntelligent building management systems rely on sensors that, when faulty, can transmit erroneous data, disrupting predictive algorithms. For example, a faulty temperature sensor can lead to excessive energy consumption and reduce occupant comfort. Predictive maintenance, while useful, does not always offer instant correction, leaving automated systems to deal with corrupted data.
To overcome these shortcomings, it is necessary to develop robust models capable of maintaining their performance in the presence of noise in the data. These models would complement predictive maintenance, enabling more efficient management of buildings, even when sensors fail.
The aim of the internship is to design and evaluate robust prediction models adapted to the specific characteristics of intelligent buildings, characterized by heterogeneous and often disturbed data. The objectives include:
- Analysing the impact of noisy data on predictions.
- Developing models capable of tolerating these disturbances.
- Proposing a hybrid approach combining model robustness and predictive maintenance.
The ideal candidate for this internship should be a final-year engineering student or Master's in computer science, data science, or artificial intelligence. Required skills include knowledge of machine learning and proficiency in Python and data science libraries (Numpy, Pandas, Tensorflow, Pytorch, etc.).
