Senior Technical Program Manager, SCG Efficiency

As a Senior Technical Program Manager within NVIDIA Silicon Co-Design Group (SCG), you will bridge the technical and management domains, driving the development and execution of SCG AI-driven Efficiency programs. You will collaborate with development managers, engineers, and multi-functional teams across systems, software, operations, and marketing to ensure the flawless delivery of our silicon projects.

Your key responsibilities will include:

• Program Leadership and Execution: End-to-End AI-driven Automation Solution Initiatives for continuous productivity efficiency improvement. Own the planning, development, and management of project schedules and deliverables. Ensure meticulous management of tasks, dependencies, and breakthroughs to achieve program objectives on schedule.

• Program Management on the SCG AI-driven Automation feature development lifecycle (data collection and labeling, experimentation, model training, evaluation, deployment, and monitoring) with a focus on reliability, safety, and performance.

• Design and Scope Management: Actively participate in crucial design reviews. Efficiently handle scope changes to minimize impacts on project timelines and outcomes. Champion engineering best practices in areas such as CI/CD, release management, experimentation, observability, and post-release validation for AI-powered features.

• Multi-functional Collaboration: Serve as the primary liaison for the technical team in multi-functional discussions, ensuring alignment on project achievements and go-to-production strategies.

• Risk Management: Proactively identify risks and dependencies, develop mitigation strategies, and advance issues to leadership as vital.

• Communication: Provide regular updates on program status, highlighting challenges and proposing solutions to internal partners, facilitating informed decision-making.

• Continuous Improvement: Leverage insights and standard processes from completed programs to drive continuous improvement in processes and outcomes for future projects, including tooling for AI program delivery, identifying opportunities to increase efficiency, predictability, and quality.