Teams at General Motors

Lead the technical strategy and systems engineering approach for autonomous vehicle behavior validation. Define requirements, metrics, acceptance criteria, safety evidence, and release readiness across simulation, road data, testing, and fleet monitoring. Diagnose issues across the autonomy stack, close coverage gaps, guide scalable validation tools and data workflows, make launch recommendations, and provide technical leadership across engineering, safety, legal, product, and operations teams.

Leads engineers and data scientists developing autonomy subsystem evaluation metrics, root-cause analyses, regression detection, and release decision tools. Owns roadmap, staffing, technical quality, and cross-functional alignment across planning, perception, prediction, and localization. Applies statistical evaluation, simulation and road data analysis, and VLMs/LLMs to determine how subsystem errors affect driving outcomes and communicate actionable findings to engineering and leadership.

Leads four teams responsible for evaluating autonomous-driving performance, classifying scenarios, analyzing subsystem failures, and translating results into engineering and release decisions. Owns roadmap, staffing, technical quality, metrics, statistical rigor, and stakeholder trust. Hires and develops managers, engineers, and data scientists while guiding evaluation strategy, regression detection, simulation and road-test analysis, and AI-assisted classification initiatives using VLMs and LLMs.