• Engage with cross-company teams (hardware/software engineering, product, QA, compliance) and drive alignment on release scope, milestones, risk management, and dependencies. • Guide engineering programs in all aspects of program management – planning, forecasting, documenting, scheduling, effective meetings, multi-faceted prioritization, management of dependencies, reporting, and effective handling of critical and blocking issues. • Guide engineering teams in the use of agile methodologies. • Develop and implement metrics for measuring program effectiveness and improvement areas, collect and analyze data in support of planning and data driven decisions. • Define and implement standard processes for open-source contribution and release management within the AI/ML ecosystem. • Report on overall program status, providing insights and recommendations to senior management. • Drive organizational alignment and efficiency by coordinating with multi-functional leads and streamlining processes. • Collaborate with hardware, software, and model program managers and engineering teams to implement inference libraries on existing and new hardware.