Lead strategic research and engineering initiatives in AI safety, alignment, and model reliability, with direct application to ADAS feature releases and autonomous systems.
Advance generative world models, simulation frameworks, and physical reasoning techniques to evaluate complex driving edge cases and validate system behavior.
Collaborate with global R&D teams to seamlessly transfer cutting-edge safety frameworks and machine learning algorithms into operational platforms and production pipelines.
Implement rigorous safety validation, out-of-distribution (OOD) detection, failure mode analysis, and uncertainty estimation methods to ensure robust platform integration.
Monitor emerging developments in foundation models and safety alignment, representing the organization by presenting at top-tier conferences (e.g., NeurIPS, CVPR, ICLR, ICRA) and publishing high-impact research.
Provide expert technical counsel to senior leadership to guide strategic R&D roadmaps, investment decisions, and patent portfolio growth in trustworthy AI.