Software Engineer, Engineering Simulation & Automation (Vehicle Engineering)

Be a member of the AI for Vehicle Engineering team, focusing on developing automated simulation tools and pipelines to accelerate engineering for our launch vehicles and spacecraft and generate high-quality training datasets for surrogate models at scale. 

Our team builds AI systems that accelerate engineering analysis, simulation, development, testing, avionics design, flight data review, logistics, and mission operations. Your work will directly support the world’s largest communication and AI satellite constellations, accelerate rapid reuse of the Falcon launch vehicle, and contribute to the development of the world’s largest rocket capable of sending humans to Mars.

In this role, you will design, develop, and maintain scalable simulation automation pipelines that create the large, diverse, and well-curated datasets required to train production-grade AI surrogate models. You will also work closely with domain experts to unblock engineering and analysis bottlenecks at SpaceX via simulation automation. You will leverage commercial, in-house, and open source simulation tools across FEA, CFD, thermal, and structural domains, writing custom scripts against their APIs to automate geometry parameterization, meshing, solving, post-processing, and data extraction at scale. You will also create general automation tools to accelerate day-to-day engineering workflows. You will work closely with ML surrogate modeling engineers, domain experts, and hardware engineers to ensure generated data and tools optimally support AI surrogates and broader engineering productivity.

• →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
• →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
• →Stay current with advances in simulation automation, meshing technology, and best practices for ML-ready datasets

• Bachelor’s degree in engineering, computer science, data science, math, physics, or a related technical discipline; OR 4+ years of professional experience building software or simulation pipelines in lieu of a degree
• 1+ years of software development experience
• 1+ years of hands-on experience with at least one simulation domain (CFD, FEA, thermal, structural analysis, etc.)

• Ability to work extended hours and weekends as necessary

• To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.  

SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.

Applicants wishing to view a copy of SpaceX’s Affirmative Action Plan for veterans and individuals with disabilities, or applicants requiring reasonable accommodation to the application/interview process should reach out to EEOCompliance@spacex.com. 

• Experience with ANSA, Star-CCM+, OpenFOAM, Abaqus, OpenTD, OpenFOAM, CalculiX or similar commercial/in-house/open source simulation tools
• Strong proficiency scripting simulation APIs (especially ANSA Python API or Star-CCM+ automation)
• Demonstrated success building automated workflows that run thousands of simulations for dataset generation
• Understanding of Design of Experiments (DOE) and sampling techniques such as Latin Hypercube (LHS)
• Experience working in HPC environments with job schedulers such as Slurm or equivalent
• Familiarity with surrogate modeling concepts and the data requirements of neural operators, FNOs, physics-informed ML, or similar models
• Familiarity with deep learning and preparing data for ML workflows
• Proficiency with Python for scientific computing and automation
• Experience developing on Linux systems
• Strong understanding of version control, testing, continuous integration, build, deployment, and monitoring
• Good understanding of statistics, numerical methods, and core engineering simulation techniques