Airframe Data Scientist – Robust AI/ML

About the role

The Airframe Data Scientist will join the Structures – Aerostructure Data Management team to develop robust AI/ML solutions that enhance airframe design, analysis and lifecycle management. Working at the intersection of physics‑based modelling and data‑driven techniques, you will help accelerate simulations and improve decision‑making for aerospace structures.

Key responsibilities

• Develop surrogate models to speed up structural simulations.
• Implement hybrid physics‑plus‑data and scientific machine‑learning approaches.
• Explore and apply large language models (LLMs) to support finite element analysis workflows.
• Use computer‑vision techniques for automated CAD/mesh quality inspection.
• Engineer data pipelines and build knowledge graphs from legacy engineering documents.
• Ensure rigorous verification, validation and uncertainty quantification (VVUQ) of AI/ML solutions deployed within the airframe domain.
• Deploy AI applications on cloud platforms such as AWS, GCP, Skywise or on‑premise environments.

Required profile

• Strong background in machine learning, deep learning and data‑driven modelling.
• Experience with scientific computing and familiarity with structural engineering concepts is a plus.
• Ability to work independently and collaborate with multidisciplinary engineering teams.

Required skills

• Python, Julia, C#, JavaScript
• Machine‑learning frameworks: Scikit‑Learn, Keras, TensorFlow, PyTorch, LangChain, FEniCS
• Surrogate modelling, hybrid modelling, scientific machine learning
• Computer‑vision for CAD/mesh inspection
• Natural language processing, generative AI, knowledge‑graph creation, semantic reasoning
• Verification, validation and uncertainty quantification (VVUQ) for AI/ML models
• Cloud platforms: AWS, GCP, Skywise or equivalent on‑premise environments