Base Salary
$125k - $175k/yr
Responsibilities
- Develop and maintain automated simulation pipelines that generate training datasets for AI surrogate models at scale.
- Build custom tools with domain engineers to reduce manual effort and improve engineering productivity.
- Automate geometry variation, meshing, batch simulation execution, post-processing, and result extraction through simulation APIs.
- Orchestrate large-scale simulation campaigns on HPC clusters using job schedulers and workflow managers.
- Collaborate with ML engineers to improve dataset quality and diversity for surrogate models.
- Implement data cleaning, metadata tagging, data management, and versioned storage of simulation results.
- Develop automation tools for simulation, analysis, design, and testing workflows.
- Ensure simulation setups are accurate, robust, and efficient for surrogate-model training.
- Integrate simulation tools with version control, CI/CD pipelines, and monitoring systems for reproducible datasets.
- Stay current with simulation automation, meshing technology, and ML-ready dataset practices.
Requirements
- Bachelor’s degree in engineering, computer science, data science, mathematics, physics, or a related technical discipline, or 4+ years of professional experience building software or simulation pipelines in lieu of a degree.
- At least 1 year of software development experience.
- At least 1 year of hands-on experience in a simulation domain such as CFD, FEA, thermal, or structural analysis.
- Experience with simulation tools such as ANSA, Star-CCM+, OpenFOAM, Abaqus, OpenTD, or CalculiX is preferred.
- Strong scripting experience with simulation APIs, especially the ANSA Python API or Star-CCM+ automation, is preferred.
- Experience building automated workflows running thousands of simulations for dataset generation is preferred.
- Understanding of Design of Experiments, Latin Hypercube sampling, statistics, numerical methods, and engineering simulation techniques is preferred.
- Experience with HPC environments and job schedulers such as Slurm is preferred.
- Familiarity with surrogate modeling, neural operators, FNOs, physics-informed machine learning, deep learning, and ML data preparation is preferred.
- Proficiency with Python for scientific computing and automation and experience developing on Linux systems are preferred.
- Understanding of version control, testing, continuous integration, build, deployment, and monitoring is preferred.
- Must be able to work extended hours and weekends as necessary.
- Must meet ITAR eligibility requirements or be eligible to obtain the required authorizations.
Benefits
- Comprehensive medical, vision, and dental coverage.
- 401(k) retirement plan, disability insurance, life insurance, paid parental leave, discounts, and other perks.
- Accrual of 3 weeks of paid vacation and eligibility for 10 or more paid holidays annually.
- Full-time role may require extended hours and weekends as necessary.
- ITAR eligibility or ability to obtain required U.S. Department of State authorizations is required.
Categories
About SpaceX
SpaceX designs, manufactures and launches the world’s most advanced rockets and spacecraft. The company was founded in 2002 by Elon Musk to revolutionize space transportation, with the ultimate goal of making life multiplanetary. SpaceX has gained worldwide attention for a series of historic milestones. It is the only private company ever to return a spacecraft from low-Earth orbit, which it first accomplished in December 2010. The company made history again in May 2012 when its Dragon spacecraft attached to the International Space Station, exchanged cargo payloads, and returned safely to Earth — a technically challenging feat previously accomplished only by governments. Since then Dragon has delivered cargo to and from the space station multiple times, providing regular cargo resupply missions for NASA. For more information, visit www.spacex.com.