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The role involves designing and operating a scalable Software Defined Networking (SDN) service for NVIDIA's Cloud infrastructure. Responsibilities include developing network architectures, ensuring performance and security, crafting Infrastructure-as-a-Service for networking, and overseeing operational aspects of the SDN service. The position requires deep expertise in host networking, Kubernetes, Linux networking, and network monitoring systems.

As a Principal Software Engineer at NVIDIA, you will lead the development of visual AI software, invent and prototype tools and services, optimize production code for GPUs, and collaborate with research teams to advance computer vision technologies. Your role involves mentoring, project planning, and driving innovation in AI applications.

As a Principal Software Architect at NVIDIA, you will enhance GPU Networking for AI workloads, lead architectural designs, conduct proof-of-concept developments, and evaluate new technologies for alignment with business goals, with a focus on high-performance computing and data centers.

As a Senior Compiler Engineer at NVIDIA, you will design, develop, and optimize compilers for AI and HPC workloads. You'll work on improving compiler software for NVIDIA Grace CPUs, collaborate with partners, and engage with open source communities to enhance performance-critical software.

As a Senior Software Architect at NVIDIA, you will design and develop solutions for network programmability, collaborate with various teams on accelerating technologies, and engage in proof-of-concept development across multiple fields related to modern data centers.

The ASIC Verification Engineer will be responsible for verification of IP/Cluster/SOC designs for NVIDIA's Graphics Processors and Tegra SOCs. This includes creating regression plans, performing pre-silicon validation, and ensuring functional coverage. Collaboration with hardware architects, software teams, and post-silicon verification is also required.

The Chip Power Optimization Engineer at NVIDIA develops advanced power models for GPUs and SOCs, estimating power consumption based on various use cases. Responsibilities include collaborating with cross-functional teams to optimize power/performance configurations and contributing to improvements in performance and power efficiency.