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Design and manage large-scale GPU clusters to support AI workloads, ensuring high uptime and quality service. Automate infrastructure provisioning and monitor performance across a multi-cloud environment. Collaborate with teams to improve operational excellence and resolve incidents.
The Principal Data Scientist will lead a team in building analytics solutions for NVIDIA's GeForce NOW cloud gaming service. Responsibilities include using AI/ML models for insights and optimizations, deploying scalable solutions for user diagnostics, and enhancing productivity through data-driven insights. The role requires collaboration with leadership to design and implement effective tech solutions for cloud gaming experiences.
The Technical Product Manager for CUDA Python will define the vision and strategy for integrating Python with the CUDA platform, collaborating with internal teams and the open-source community to improve GPU programming for developers. Responsibilities include market analysis, product roadmap creation, and go-to-market strategy development.
In this role, you'll innovate and architect low power solutions for GPUs, collaborating cross-functionally to enhance energy efficiency across platforms. Responsibilities include designing and verifying features for improved battery life, contributing to power performance modeling, and engaging in architectural studies and tradeoff analyses.
Develop and maintain software for GPU communication, manage and troubleshoot extensive GPU clusters, automate deployment and maintenance processes, and collaborate with engineering teams to enhance cluster operations.
As a Senior System Software Engineer at NVIDIA, you will develop and verify innovative PCIe drivers and middleware, ensuring high efficiency and low latency. You'll collaborate with multi-functional teams, provide customer support, and engage in cutting-edge technology environments, contributing to advancements in computing systems.
The Senior Solution Engineer will provide support for NVIDIA's vGPU and Omniverse products, triaging customer issues, collaborating with engineering to resolve complex problems, and developing features and tools as part of the solution engineering efforts. The role demands excellent communication skills and a deep understanding of virtualized/cloud infrastructure.
As a Distinguished Engineer at NVIDIA, you will lead AI Resiliency by architecting and developing robust software features for AI model training on large superclusters. Collaborating with a cross-functional team, you will innovate resilient designs and ensure optimal performance with minimal downtime. You'll also communicate progress to senior leadership, impacting critical customers.
You will analyze and improve design methodology for CDC, RDC, and STA constraints in DPUs and SOCs, driving key sign-offs and developing associated checks. Collaborate on frontend and backend assertions to support design integrity and optimization for high-speed communication devices.
As a Hardware Farm Engineer at NVIDIA, you will build and manage the global hardware infrastructure for silicon validation, oversee the functionality of the Hardware Farm, debug hardware and software issues, create test plans, and collaborate with global teams to enhance processes. You will also lead the implementation of automated monitoring systems and analyze performance metrics for optimization.
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