Technical Program Manager, EDA Compute Infrastructure

NVIDIA•Santa Clara, CA

3d•Hybrid

About The Position

Hardware Infrastructure is seeking a Senior Technical Program Manager to lead the strategy and execution of programs supporting the reliability, scalability, and modernization of infrastructure for NVIDIA's Hardware ecosystem. This infrastructure supports development and tapeout of NVIDIA chips and must be reliable, performant, and efficient for internal users. The role partners with senior management to plan future programs and works with internal customers to align across the company and achieve strong execution. It also collaborates closely with CSP and software tooling partners, and develops standardized planning, reporting, execution methodologies, and metrics to meet challenging objectives in a fast-paced environment.

Requirements

Bachelor's degree or equivalent experience.
12+ years of program management experience, including demonstrated ability to manage global projects across multiple time zones.
Demonstrated skill engaging and moderating successful collaborations with engineering partners and vendors.
Exceptional communication and presentation skills for diverse technical and non-technical audiences.
In-depth understanding of software engineering principles and quality requirements in enterprise systems.
Strong multitasking abilities, thoroughness, and ability to switch contexts rapidly.
Knowledge of agile methodologies and tools, project planning, and task-tracking tools.
Proactive and enthusiastic approach to identifying and implementing positive changes in software engineering and release management in a fast-paced environment.

Nice To Haves

Background in computer science, machine learning, deep learning, open-source software, infrastructure technologies, or GPU technology.
Prior experience in infrastructure software, production application software development, software development, release and support methodology, or DevOps.
Prior experience managing customer workflows using large-scale distributed computing and working with AI researchers or directly training AI models.
Consistent track record of driving process improvements and measuring efficiency.
Passion for sharing knowledge and experience driving complex projects end-to-end.

Responsibilities

Engage with cross-company partners to plan programs and coordinate teams in meeting key business objectives.
Guide engineering programs across planning, forecasting, documentation, scheduling, meetings, prioritization, dependency management, reporting, and handling critical or blocking issues.
Guide engineering teams in using agile methodologies.
Develop and implement metrics to measure program effectiveness and identify improvement areas; collect and analyze data to support planning and data-driven decisions.
Report overall program status and provide insights and recommendations to senior management.
Drive organizational alignment and efficiency by coordinating with multifunctional leads and streamlining processes.
Guide teams designing for advanced, complex, competing, and conflicting customer requirements.
Moderate technical discussions and help bring them to successful conclusions.
Act as a liaison between developers and customers and between technical and non-technical audiences.
Promote continuous improvement and identify opportunities for process enhancements.