The opportunity
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.
What you'll do
Develop and maintain automated simulation pipelines that generate training: datasets for AI surrogate models at scale
Partner with domain engineers to identify bottlenecks and build custom tools: that improve productivity and reduce manual effort
Create and optimize scripts using APIs such as ANSA Python API, Star-CCM+: Java/Python macros, OpenTD, Abaqus, or equivalent tools
Build parametric workflows for geometry variation, automated meshing, batch: simulation execution, and result extraction
Orchestrate large-scale simulation campaigns on HPC clusters using job schedulers and workflow managers
Collaborate closely with ML engineers to understand dataset requirements and: iteratively improve data quality and diversity
What they're looking for
- Implement data management, cleaning, metadata tagging, and versioned storage of simulation results
- Develop general automation tools and scripts to accelerate engineering: workflows across simulation, analysis, design, and testing tasks
- Deep dive into engineering physics domains to ensure simulation setups are: accurate, robust, and efficient for surrogate training
- Integrate simulation tools with version control, CI/CD pipelines, and: monitoring systems for reproducible datasets