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As a Data Center Power Test Architect at NVIDIA, you will be a key technical leader driving quality and reliability across our next-generation datacenter software and firmware stack.
Develop and deploy scalable GenAI applications that integrate with existing workflows and enhance overall productivity. Use state-of-the-art AI tools and techniques to accelerate GPU/ SOC Architecture modeling.
In this role, you will be working on supporting CUDA Tile, a new tile-based programming model, for NVIDIA LPUs. CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( https://developer.nvidia.com/cuda/tile ).
Define test strategy and test validation plans for CSP integration milestones, partner with hyper scalars to understand their test methodology, identify gaps and provide NVIDIA recommendations. Reproduce, characterize, and triage customer bugs in the customer environment.
Drive the product vision and roadmap for Omniverse rendering capabilities, ovrtx, and sensor simulation workflows.
Own product marketing and positioning of NVIDIA desktop products with precision. Lead cross-functional teams to execute business-critical go-to-market strategies, from planning through launch and post-launch optimization.
Build scalable mapping systems using crowdsourced perception data and multi-camera video collected from a vast number of vehicles. Develop 3D reconstruction, structure-from-motion, pose estimation, and multi-view geometry algorithms for large-scale road scene understanding.
Analyze developer journey needs with product teams and domain experts to identify and close gaps for both human and agent workflows using CUDA-Q.
Lead and manage the entire silicon-based products lifecycle, including planning, delivery of key milestones, and ramp of products into mass production. Collaborate with engineering, design, and marketing teams to define project objectives, requirements, and deliverables.
Act as comp business partner, strategic solution provider and specialist advisor to global recruiting teams, HRBPs and business unit leaders by combining in-depth knowledge of compensation principles, understanding of the business and market landscape.
Lead the strategic direction and product vision for NVIDIA’s Ethernet networking hardware and silicon platforms, driving product planning, execution, lifecycle management, and technology transitions.
Work with us to translate driving-feature needs and safety analysis into world-model requirements, performance targets and error budgets. Investigate real-world failure modes and develop metrics, scenarios and tests that expose gaps across operating conditions.
Ability to resolve sophisticated customer concerns and technical issues through meticulous research, reproductions, and solving problems for customers installing our products and supporting systems using Linux Operating Systems (multi-distro), with the focus on NVIDIA Ethernet…
Collaborate cross-functionally with system architects, hardware, firmware/software, process/reliability, and operations teams to co-design system-level speed features and deliver industry-defining products.
Lead the full lifecycle of an autonomous driving carline program, specialized in L4 Robotaxi productization, from feature definition and platform planning to vehicle-specific adaptation, prototype integration, validation, and mass-production readiness.
Shape the architecture of the hardware abstraction layers and core system libraries, and own the API contracts for the components you lead. Design and implement drivers, runtimes, and data movement and aggregation pipelines that execute workloads on novel silicon.
Build and deepen technical expertise within oil, gas, nuclear, solar, wind, and emerging clean technologies sectors. Serve as a trusted technical advisor and resource for energy developers.
Planning and performing DDR memory tuning, validation, and feature enablement on NVIDIA products. Reviewing silicon design specifications, component datasheets, board schematics, and layout.
Serve as the primary embedded systems expert for NVIDIA Physical AI partners using technologies such as Jetson, Holoscan, Isaac ROS, Isaac OS, GR00T.
Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure.
Crafting and implementing high-performance Vision AI pipelines for real-time and streaming scenarios using brand-new computer vision and deep learning models.
You'll be working in a distributed team that explores innovative ways to make GPU- and DPU-accelerated applications easier to develop, deploy, and monitor on the latest and greatest NVIDIA hardware.
Die-Level Logic Fault Localization: Perform complex, hands-on failure analysis and root cause identification using physical and electrical fault isolation methodologies.
Develop accurate 3D EM models for PCB and interconnect structures using tools such as HFSS. Simulate multi-layer PCB designs under cryogenic conditions. Define high-speed constraints, SI specifications, and design guidelines across RF, materials, and thermal domains.
US, USA