Professional, Engineering – Multidisciplinary Design, Analysis & Optimization (MDAO / MDO)

What are your contributions to the team?

• Design, develop, and maintain software tools dedicated to a large-scale industrial-level multidisciplinary design, analysis, and optimization (MDO/MDAO) framework. 
• Collaborate closely with aircraft design, analysis, systems, and performance teams to ensure alignment between developed tools and business needs. 
• Assume a technical leadership role in the maintenance, evolution, and continuous improvement of an existing multi‑fidelity optimizer. 
• Design, implement, and validate new algorithmic approaches within internal codebases, with a particular focus on advanced Bayesian and multi‑fidelity optimization strategies. 
• Implement optimization under uncertainty (OUU) strategies to support decision‑making in the presence of epistemic and aleatory uncertainties, and assess their impact on aircraft performance, design margins, and technical risks. 
• Perform advanced statistical analyses, including sensitivity analyses and uncertainty propagation. 
• Develop and train machine learning models to support optimization, performance prediction, and uncertainty quantification. 
• Integrate machine learning models, optimization algorithms, and statistical methods within the company’s Digital Engineering environment. 
• Present results, methodological choices, and technical orientations to senior experts, fellows, and decision‑making bodies. 
• Conduct active technological and scientific reviews in MDO, Bayesian optimization, uncertainty quantification, and optimization under uncertainty in order to influence the technical roadmap. 
• Supervise interns. 

How to thrive in this role?

• You hold a Master’s degree or Ph.D. in Aerospace Engineering, Mechanical Engineering, Applied Mathematics, Scientific Computing, or a related field. 
• You have a specialization in Multidisciplinary Design, Analysis, and Optimization (MDO/MDAO), including the usage of MDO frameworks (openMDAO, GEMSEO, etc.) 
• You demonstrate a strong expertise in multi‑fidelity optimization methods and an excellent understanding of Bayesian methods, including Bayesian optimization and probabilistic models, which are essential for this role. 
• You can understand, analyze, and synthesize scientific publications in order to translate state‑of‑the‑art methods into algorithmic solutions applicable in an industrial context. 
• You are comfortable with software development, including version control using Git and CI/CD practices. Experience with software development assisted by AI agents is considered an asset. 
• You have experience with High-Performance Computing (HPC) and cross-platform (Windows, linux) computing. 
• You have experience or a strong interest in integrating advanced tools and software within a Digital Engineering environment. 
• You have knowledge or experience with uncertainty quantification (UQ) and optimization under uncertainty (OUU) approaches, which is considered an asset. 
• You demonstrate a strong understanding of machine learning concepts, including supervised and unsupervised approaches, as well as principles of training, validation, hyperparameter tuning, and model evaluation. This is considered an asset. 
• You have a good understanding of aircraft systems, their interactions, and their impact on aircraft configuration and structure. 
• You are open‑minded, curious, rigorous, and methodical. 
• You seek a harmonious and cohesive team environment and value knowledge sharing among team members. 
• You have excellent analytical and problem‑solving skills. 
• You have strong communication skills and can easily adapt your communication to your audience.