Sr. Software Engineer, Propulsion Simulation & Data Analysis (Raptor)
Hawthorne, CAfull time
On Site
senior
$165k–$230k
H1B: no
SpaceX Sr. Software Engineer for Propulsion Simulation & Data Analysis at SpaceX focusing on the Raptor engine. Responsible for maintaining and improving physics models and conducting engine cycle analysis to support design and anomaly resolution.
Responsibilities
Maintain and improve the accuracy of the lumped-parameter thermofluid physics model of the Raptor engine
Conduce engine cycle analysis to steer future-state engine design and thrust upgrades
Conduct anomaly resolution utilizing the engine model and sparse instrumentation
Develop a detailed understanding of the physics underlying rocket engine performance, sources of performance variability, as well as related modeling 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 the 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 as well as to standardize hardware and software practices, tools, and methods to maximize functionality and value while minimizing future overhead and obsolescence
Qualification
Bachelor's degree in computer scienceDynamical systems modelingData driven analysis of complex systems
Required
Bachelor's degree in computer science, engineering, or a STEM discipline
5+ year experience writing computer software
5+ year experience with physics-based simulations of real dynamic systems
Preferred
Dynamical systems modeling
Experience with lumped parameter modeling 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 the basic principles of 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 sanitization, curation, visualization, exploration to high dimensional datasets
