Machine Learning Engineer - Benguerir
Secteur de l’entreprise : Enseignement / Formation
ENTREPRISE :
Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco’s frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.
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Culture de l'entreprise :
UM6P – Université Mohammed VI Polytechnique se caractérise par une culture fortement orientée innovation, où la créativité, l’expérimentation et l’audace intellectuelle constituent des piliers essentiels. L’université encourage l’initiative, l’ouverture d’esprit et l’autonomie, dans un environnement stimulant tourné vers la recherche, l’entrepreneuriat et l’impact. Cette dynamique innovante est enrichie par une dimension coopérative solide, valorisant la collaboration, le partage des savoirs et le développement humain. Une orientation vers la performance et l’excellence complète l’ensemble, tandis que les processus formels restent volontairement plus légers pour préserver l’agilité.
Poste :
Machine Learning Engineer
Location: The UM6P Vanguard Center, Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco
Job Type: CDD convertible en CDI
Number of Positions: 1
About Us:
The UM6P Vanguard Center is at the forefront of technological innovation, focusing on advanced research and practical applications in fields such as mechatronics, embedded systems, AR/VR, cybersecurity, and digital twins. As we expand our activities, we are seeking a skilled Machine Learning Engineer to build predictive models and algorithms that enhance the functionality and accuracy of our digital twin systems.
Position Summary:
We are seeking a talented Machine Learning Engineer to develop predictive models and algorithms for digital twin applications. The ideal candidate will leverage data from various sources to enhance the functionality and accuracy of digital twins.
Key Responsibilities:
- Develop and implement machine learning models and algorithms for digital twin systems.
- Collaborate with cross-functional teams to gather data requirements and develop solutions.
- Perform data preprocessing, feature engineering, and model evaluation.
- Optimize machine learning models for performance and scalability.
- Document methodologies, results, and project progress.
- Stay current with emerging machine learning technologies and industry trends.
- Participate in team meetings and contribute to brainstorming sessions.
What We Offer:
- A stimulating and innovative work environment at a leading research institution.
- Opportunities for professional growth and development.
- Access to state-of-the-art facilities and resources.
- Collaborative and supportive team culture.
- Competitive salary and benefits package.
Profil recherché :
Qualifications:
- Master’s degree or Engineering School in Computer Science, Data Science, Applied Mathematics, or a related field.
- Strong understanding of machine learning principles and best practices.
- Proficiency in programming languages such as Python or R.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Excellent problem-solving skills and attention to detail.
- Strong communication skills and the ability to work collaboratively in a team environment.
- Eagerness to learn and adapt to new challenges and technologies.
Preferred Qualifications:
- Experience with big data technologies (e.g., Hadoop, Spark).
- Knowledge of deep learning and neural networks.
- Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud).
- Hands-on experience with data visualization tools (e.g., Tableau, Power BI).
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