Develop diagnostic systems for NVIDIA data center platforms, which involve hardware and software tools to develop the worst case stress workloads for CPUs, GPUs, memory, storage, and interconnects.
Architect and build scalable, reliable systems for agentic AI, spanning agent runtimes, harnesses, inference, evaluation, and orchestration.
Lead and implement all aspects of software planning and completion for SOC chips - coordinate the software POR, pre-silicon development, pre-silicon software validation, bring-up and productization.
Establish yourself as a technical specialist in AI networking products, specifically the BlueField DPU and ConnectX product lines. Architect, design, and develop innovative, scalable, and high-performance hardware-accelerated software solutions.
Drive the design, build, launch and operation of our services, tools and open-source projects. Plan and assign the team’s work, mentor junior engineers and review designs.
Lead technical activities for new product introductions at scale with focus on hybrid deployments between cloud and on-prem.
You will lead software activities for NVIDIA's deep learning server platforms, from design through production; collaborating with teams across company to deliver software solutions. Drive the system architecture for a complex server platform in a multi-functional environment.
Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters. Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
NVIDIA · 15d ago
Develop CUDA Compute test plans and coordinate validation across PCIe high-performance computing GPUs, NVIDIA systems, OEM servers, GPU configurations, operating systems, driver modes, CUDA versions, and release stages.
Modernize PAM, secure infrastructure access, and NHI services for NVIDIA’s agentic era, covering privileged users, service accounts, AI/coding/service agents, and autonomous workflows.
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