The role involves defining roadmaps for high-performance and low-latency pipelines that connect large-scale simulation with real-world monitoring. The individual will manage and mentor a team of engineers to foster technical excellence and continuous learning. Responsibilities include driving scientific rigor in virtual driver testing to ensure simulation signals predict real-world behavior. The position requires leading the integration of machine learning models to identify driving scenarios and optimize testing efficiency. Additionally, the role ensures the stability of production systems while partnering with cross-functional teams to translate vehicle telemetry into strategic insights.

Candidates must possess at least five years of full-time software engineering experience or a quantitative PhD with two years of professional experience. The role requires experience managing small teams and an advanced command of C++ or another object-oriented programming language. Proficiency in Python and SQL is also necessary. While a degree is not strictly mandated, the company prefers candidates holding a B.Sc., M.Sc., or PhD in Computer Science.