Description
As a Manager, System Design Tools and Methodology at NVIDIA, you will lead a team of developers in CAD, PLM, and data examination to bridge the gap between electronic, mechanical, and thermal domains. This is a high-impact leadership role that will build our future by optimising multi-disciplinary engineering ecosystems.
Key responsibilities include: Driving the evolution of CAD and PLM ecosystems to support rapid, high-fidelity hardware iteration across the enterprise. Architecting data-driven workflows and analytics platforms that provide real-time insights into system design health and project achievements. Partnering with a diverse engineering landscape, including electronic, mechanical, thermal, and validation teams, to eliminate technical friction. Streamlining the transition from prototyping to manufacturing through the implementation of robust, scalable methodologies. Collaborating closely with project and program managers to identify and automate bottlenecks throughout the process of bringing products to market. Leading a high-performance team focused on developing custom utilities, API integrations, and advanced reporting tools that empower thousands of engineers.
Requirements include: Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science, or equivalent experience. 10+ overall years of total experience in system design, CAD administration, or PLM workflow development. 4+ years of direct people management or technical leadership experience within a complex engineering environment. A comprehensive understanding of the hardware product development lifecycle (PDLC), from conceptual design to mass production operations. Demonstrated ability to lead and influence multi-functional collaborators across engineering, operations, and applications teams. Strong technical background in implementing or customizing enterprise-level engineering tools (e.g., Dassault, Cadence, PTC, or similar). Experience employing data analytics to drive process improvements and engineering efficiency.
Preferred qualifications include: Consistent record of running multi-disciplinary CAD environments with a focus on ECAD/MCAD integration. Experience using Python or other scripting languages to develop custom automation and extend tool functionality. Background in large-scale PLM migrations or implementing company-wide NUDD (New, Unique, Different, Difficult) risk management frameworks. Knowledge of modern data visualization tools for translating complex engineering metrics into actionable executive insights.