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Design and implement APIs, state management, and workflow automation for NVIDIA's DGX Cloud. Integrate container orchestration and observability tools, build schema-driven platforms, optimize cloud reliability and telemetry, and lead scalable infrastructure projects across teams.

Design and implement developer tools for GPU-based 3D graphics and neural rendering. Improve existing tooling, collaborate with compiler/driver/research teams, write high-performance C/C++ code, document designs, estimate tasks, and develop test plans with QA.

Lead GPU ASIC development from concept through mass production. Coordinate architecture, RTL, verification, physical implementation, packaging, test and silicon bring-up. Track milestones, mitigate technical risks, and align cross-functional teams across IP, software, emulation, VLSI, and test to deliver high-performance GPU processors for AI datacenter products.

As an HR Business Partner at NVIDIA, you will provide strategic HR support for the GPU Software business, focusing on staffing, performance management, and employee development.

Drive physical design of high-frequency, low-power CPUs/GPUs/SoCs at block, cluster, or full-chip level with emphasis on netlist quality: equivalence checking/formal verification, CDC and MTBF analysis, logic synthesis, timing convergence, STA, constraint generation/management, and ECO implementation. Use industry-standard EDA tools and scripting to debug and improve flows.

Design next-gen GPU systems, architect features with software and hardware teams, create functional models in C++, and support validation activities.

Lead implementation of AI infrastructure solutions on NCP/Neo Cloud and DGX Cloud. Deploy and optimize distributed training/inference, manage Kubernetes/GPU scheduling, profile and tune large-scale workloads, implement reference architectures and integrations, build runbooks and monitoring, and provide remote and on-site technical support to strategic customers.

Lead verification for GPU/SoC display IP: define verification scope and testplans, build UVM-based infrastructure, develop UVM and C/C++ testbenches, drive coverage closure, debug silicon integrations, and collaborate with architects, partners, and customers globally.

Lead NVIDIA's engagement with public-sector wireless research to advance 6G and AI-native RAN projects. Build partner relationships, represent NVIDIA in standards bodies (ATIS, AI-RAN, 3GPP), collaborate cross-functionally, analyze RAN challenges, and drive technical strategies and deliverables aligned with NVIDIA's platform and quality standards.

Lead and coordinate global software programs for deep learning training and inference frameworks. Drive cross-functional alignment, manage schedules, risks, and dependencies, implement release and open-source processes, define metrics, report status to senior management, and improve program execution across hardware, software, and infrastructure teams.