Sr. Software Engineer, Propulsion Simulation & Data Analysis (Raptor) Verified today
Sr. Software 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 develop rapid, seamless processes to translate engine test data into accurate predictions of future performance. Your models and analysis are relied upon daily to evaluate safety and optimality of flight trajectories, and guide both engine design and every mission and engine test.
Responsibilities
- Maintain and improve 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 utilizing the engine model and sparse instrumentation
- Develop detailed understanding of physics underlying rocket engine performance, sources of variability, and related modeling and measurement techniques
- Maintain and improve the Raptor engine representation 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 hardware design
- Automate processes and software tools used to predict test performance and generate flight performance predictions for GNC (guidance, navigation, and control) and flight software
- Collaborate across the company to extend and improve tool interoperability and standardize hardware and software practices
Basic Qualifications
- Bachelor's degree in computer science, engineering, or a STEM discipline
- 5+ years experience writing computer software
- 5+ years experience with physics-based simulations of real dynamic systems
Preferred Skills and Experience
- Dynamical systems modeling
- Lumped parameter modeling of physical systems
- Physics-informed neural networks applied to real-world engineering problems
- Data-driven analysis of complex systems
- Root cause inference from sparse measurements
- Compressible and incompressible flow, thermodynamics, thermochemistry, mechanics, and materials
- Written and verbal communication skills and presentation ability
- Data pipelines providing sanitization, curation, visualization, and exploration of high-dimensional datasets