Missions
Airbus is pleased to offer a V.I.E. position in Madrid, Spain. This initiative provides a unique opportunity to acquire specialized professional competencies within a global aerospace leader, fostering both technical mastery and cross-cultural leadership skills.The Role & Strategic Objective
The selected candidate will be integrated into the Airworthiness area, gaining a comprehensive 360-degree perspective on the lifecycle of aircraft safety. You will bridge the gap between real-world aviation impact and advanced AI theory, contributing to the continued airworthiness and certification of the Airbus fleet.
By diving into operational systems—including Auxiliary Power Units (APU) , Exterior Lighting, and Bleed systems—you will play a pivotal role in ensuring the seamless and safe operation of our global fleet.
Key Responsibilities
Certification & Safety: Support the certification of systems modifications and conduct rigorous investigations into airline safety occurrences to enhance fleet-wide security.
Advanced Data Modeling: Analyze large-scale flight operation datasets to identify patterns, anomalies, and predictive indicators for daily operational excellence.
AI Model Development: Architect and implement machine learning models (e.g., predictive maintenance, anomaly detection, NLP) to optimize airworthiness activities.
Algorithmic Optimization: Conduct research and testing to optimize AI algorithms for high-performance accuracy and scalability within a critical aviation context.
Technical Reporting: Synthesize complex methodologies and results into clear, concise documentation for presentation to multidisciplinary engineering teams
Profil recherché
We are seeking candidates with a Master’s Degree in Aerospace Engineering with knowledge in Computer Science, Data Science, Electrical Engineering, Applied Mathematics, or a related technical discipline.Technical Requirements:
Aerospace Knowledge: Familiarity with aircraft systems and aerospace engineering principles.
Programming Proficiency: Advanced command of at least one major AI/ML language (e.g., Python) .
AI/ML Expertise: Practical experience with machine learning frameworks, libraries, and fundamental principles.
Knowledge on software and cloud engineering practices
Soft Skills: Strong analytical capabilities, meticulous attention to detail, and the ability to operate effectively in both autonomous and collaborative environments.
Linguistic Proficiency: Professional-level written and verbal communication skills in English