Simulation Engineer Intern

LLM Integration: Leverage Large Language Models (LLMs) to architect and implement a pipeline that automatically generates realistic, highly structured driving scenarios.

Translate ODDs to Prompts: Convert complex Operational Design Domains (ODDs) and safety/NHTSA guidelines into effective prompt frameworks and programmatic constraints for the model.

Simulation Integration: Interface the LLM-generated scenarios directly with the autonomous vehicle simulation environment to create executable, varied testing grounds.

Apply Deontic Logic: Incorporate rule-based constraints (deontic logic) to ensure the generated scenarios strictly adhere to or properly test complex traffic laws, rights-of-way, and safety protocols.

Quality Assurance & Iteration: Collaborate with the simulation and machine learning teams to evaluate the realism, diversity, and edge-case coverage of the synthetic scenarios, refining the models as needed.