Systems Airworthiness & Artificial Intelligence Specialist (H/F)

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.

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.