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Verify GPU and SoC RTL, architectures, and golden models using emulation/prototyping. Define verification scope, build testbenches and infrastructure, debug RTL, develop verification tools, and collaborate with architects, designers, and software teams to ensure design correctness.

Create developer-focused technical content, demos, reference examples, deployment guides, and docs-as-code workflows to accelerate adoption of NVIDIA enterprise AI software. Work across engineering, product, field, and partners to design developer journeys, build sample applications and notebooks, enable sales and partners, capture feedback, and engage the open source and cloud-native communities.

Lead DFM/DFA efforts for mechanical and thermal components from concept through mass production. Identify and resolve manufacturability issues, collaborate with suppliers and CEMs, develop assembly fixtures, drive corrective actions and yield improvements, perform failure analysis, and support manufacturing R&D, automation, and NPI processes.

Partner with engineering, product, and sales to design and deliver GPU-accelerated ML/HPC solutions for capital markets. Lead POCs, profile and optimize ML/DL models on NVIDIA GPUs, collaborate with client researchers to deploy models at scale on cloud or on-prem HPC, and produce technical collateral (notebooks, blogs) to drive adoption.

Provide technical customer enablement for NVIDIA datacenter products: create hardware design collateral, review server designs (thermal, mechanical, electrical, SI/PI), perform hardware debug and lab validation, reproduce and track issues, and work cross-functionally to resolve system integration problems for x86 and ARM server platforms.

Lead a team to design and deliver system-level manufacturing test solutions, develop test strategies, automation, scripts and fixtures, debug HW/SW issues, and improve production test efficiency across GPU and data center products.

Serve as the embedded systems expert for NVIDIA Physical AI partners, integrating sensors, deploying and optimizing robotics foundation models on Jetson-class edge hardware, guiding customers from prototype to production, and delivering reference implementations and workshops.

Lead developer marketing programs to acquire, activate, and grow developers building AI applications on PC using NVIDIA SDKs and RTX. Create technical content, run community and partner activations, educate developers on platform capabilities, drive engagement and evangelism across channels, and use analytics to improve program performance.

Design, implement, and maintain the cluster-manager for large-scale block storage. Develop lifecycle and RAID management features, debug production C/C++ code, coordinate QA testing, analyze customer issues, and collaborate with networking, hardware, and external teams to deliver high-performance, highly scalable storage services.

Conduct research and implement novel methods for efficient deep learning (pruning, quantization, NAS, adaptive inference, resource-efficient training). Publish results, collaborate across teams, mentor interns, present at conferences, and help transfer research into NVIDIA products.