MDAO Engineer

Job description

Job responsibilities

• Develop reusable engineering models, software components, and computational workflows for multidisciplinary vehicle analysis and optimization.
• Architect and extend the computational architecture and interfaces that connect aerodynamics, propulsion, structures, mass properties, controls, mission performance, and parameterized geometry.
• Develop derivative-enabled models and workflows for efficient gradient-based optimization, including appropriate methods for computing and verifying sensitivities.
• Build and maintain practical software and model-development practices, including clear interfaces, version control, documentation, automated testing, reproducibility, and validation.
• Develop multi-fidelity analysis capabilities using higher-fidelity simulation, ground test, flight test, and operational data to improve model accuracy.
• Improve the performance, robustness, and usability of MDAO workflows as the number of models, users, and vehicle programs grows.
• Partner with conceptual design, configuration, and performance engineers to identify high-value development priorities and ensure the resulting tools support real design decisions.
• Apply and evaluate new capabilities through vehicle sizing, configuration trade, mission analysis, and performance studies as needed.

Job requirements

• Bachelor's degree in Aerospace Engineering, Mechanical Engineering, Applied Physics, or a related technical field.
• 2+ years of relevant engineering experience in engineering software, computational design, MDAO, vehicle design, or optimization.
• Experience developing engineering models, analysis software, or optimization workflows for aerospace vehicles or other complex physical systems.
• Working knowledge of aerospace vehicle design and the interactions between aerodynamics, propulsion, structures, mass properties, controls, and mission performance.
• Familiarity with conceptual design, preliminary design, configuration and sizing, mission performance, or operational performance analysis.
• Software development skills in a scientific computing language, with the ability and interest to develop reliable, reusable engineering software and work within collaborative software development practices.
• Experience verifying and validating engineering models and communicating their assumptions and limitations.
• Strong engineering judgment and the ability to collaborate effectively across technical disciplines.