Propulsion Engineer, Propulsion Simulation & Data Analysis Verified today
Propulsion Engineer, Propulsion Simulation & Data Analysis (Raptor)
The Raptor Systems Modeling and Control Team is responsible for power-balance, optimal control, and calibration of one of the world's most prolific and advanced rocket engines. You will provide data and model-driven insights supporting operations and component teams in high-consequence decision making. Your models and analysis guide the safety and optimality of flight trajectories, inform engine design, and support the operation of every mission and engine test.
Responsibilities
- Maintain and improve the accuracy of the lumped-parameter thermofluid physics model of the Raptor engine
- Conduct engine cycle analysis to steer future-state engine design and thrust upgrades
- Conduct anomaly resolution utilising the engine model and sparse instrumentation
- Develop a detailed understanding of the physics underlying rocket engine performance, sources of performance variability, and related modelling and measurement techniques
- Maintain and improve the accuracy of the representation of the Raptor engine used in integrated vehicle simulations, control software validation and flight Monte Carlo analysis
- Develop tools and portals to understand sources of engine performance variability and enact improvements to manufacturing and engine hardware design
- Automate processes and software tools that are used to predict test performance and generate flight performance predictions for GNC (guidance, navigation, and control) and flight software
- Collaborate with engineers across the company to extend and improve interoperability among existing tools and to standardise hardware and software practices, tools, and methods
Basic Qualifications
- Bachelor's degree in computer science, engineering, or a STEM discipline
- 1+ year experience with physics-based simulations of real dynamic systems
Preferred Skills and Experience
- Dynamical systems modelling
- Experience with lumped parameter modelling of physical systems
- Experience implementing physics-informed neural networks to solve real-world engineering problems
- Data-driven analysis of complex systems
- Experience inferring root cause from sparse measurements
- Demonstrable proficiency in compressible and incompressible flow, thermodynamics, thermochemistry, mechanics, and materials
- Strong written and verbal communication skills, ability to make presentations to team members, internal customers and management
- Experience building data pipelines providing sanitisation, curation, visualisation, exploration to high dimensional datasets
- Experience working with or simulating combustion engines or fluid systems