Sr. Vehicle Modeling Engineer, Applied AI Systems

What you'll do

• Build and maintain vehicle plant models and FMI-based co-simulation for model-to-code validation, SIL regression testing, and field issue replay.
• Develop LLM pipelines, semantic search, and RAG tools for requirements, test generation, coverage analysis, and root-cause analysis; integrate them with engineering systems.
• Author requirements and test cases, participate in architecture and safety reviews, and document AI-augmented engineering practices.

What they ask for

• BS/MS in Electrical, Computer, Mechanical, or Systems Engineering, or related field—or equivalent demonstrated experience through projects.
• Strong Python skills for data processing, AI workflow prototyping, automation, or microservices.
• Practical experience building LLM applications, such as RAG pipelines, semantic search, structured reasoning, or agent frameworks.
• Ability to decompose physical products into subsystems, behaviors, and interfaces, and iterate from prototype to production using modelling.

Nice to have

• Experience with physical simulation tools or FMI/FMU co-simulation; hands-on physical systems projects.
• Automotive systems engineering artifacts, LLM evaluation, GitLab CI/CD, AI engineering portfolio, or fault analysis methods.

Pay

$135.1K – $185.8K USD base salary; annual bonus target of 10% (bonus target; amount not stated)

Tools

Python, OpenModelica, Julia, Simulink, LangChain, LlamaIndex, GitLab, FMI/FMU

AI focus

Build and deploy LLM-assisted requirements and test pipelines, semantic search and RAG, AI analytics over engineering and fleet data, and integrations with GitLab and test management systems.