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Lead technical delivery for strategic Agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale.
Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters. Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks.
Primary responsibilities will include deploying, managing, and validating AI/HPC infrastructure in Linux-based environments for first of kind NVIDIA hardware.
NVIS Data Center deployment planning: Collaborate with product and engineering groups to understand NVIDIA’s reference architectures for data center infrastructure, encompassing power distribution, cooling systems, controls and monitoring, and network/cabling layout.
Architect, design, develop, and debug system software for NVIDIA Halos OS across QNX, Linux, and hypervisor-based environments. Design and develop BSP, boot, driver, device-management, diagnostics, and platform software for NVIDIA SoCs and edge AI platforms.
Architecture & Roadmap: Develop and improve the technical design, architecture, and roadmap for radar-based 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art DNN and transformer-based architectures.
Contribute to the build and development of world-class ISP to meet the ambitious performance and quality standards of NVIDIA's autonomous driving and robotics applications.
Define contamination control and fluid cleanliness standards for liquid cooling components, such as cold plates, coolant channels, manifolds, connectors, and PCB contact-pad interfaces.
Develop Java, Scala and CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON. Enable interoperability with table formats such as Apache Iceberg and Delta Lake, and metastores such as Unity Catalog.
Analyzing deep learning networks and developing compiler optimization algorithms. Strong programming skills in CUDA including analyzing and debugging performance bottlenecks on GPUs.
Lead the technical engagement with a focused set of ISV partners, working closely with their Software Platform Architects. Together you'll set the objectives, timelines, and adoption plan for each account.
Co-design and build production agentic systems hand-in-hand with a focused set of ISV Software Platform Architects. Define technical objectives, timelines, and adoption strategy aligned to their critical business objectives.
End-to-End SoC Lifecycle Ownership: Define and drive the hardware architecture from early concept through bring-up and ecosystem enablement.
Assist independent software vendors, ecosystem partners, and lighthouse customers in assessing and adopting technologies within DSX Sim, and Omniverse libraries.
Take charge of comprehensive memory quality initiatives proactively to meet and exceed NVIDIA's quality standards. Cultivate strong supplier relationships to collaborate and align on strategic quality initiatives.
Lead toolchain, build, code-health, and performance-workflow adoption projects across large software components. Evaluate and deploy supported GCC and LLVM/Clang toolchains, compiler options, linkers, sysroots, and cross-compilation configurations.
Provide direct support to our NVIDIA Enterprise customers to resolve or advance customer issues. Work with engineering teams on customer issues, providing logs, reproduction, and other triage information. Apply AI to create/update products and/or support tools.
Customer Satisfaction: Manage RMA cases and lead all aspects of replacement part fulfillment to clear the open RMA backlog per Service Level Agreements. Work with account teams to prioritize backlog in case of supply constraints.
Collaborate with NPI teams for smooth production ramp at worldwide manufacturing sites as you continuously find opportunities for potential process improvements and collaborate with multi-functional teams to implement.
Develop product level reliability qualification plan and implement the qualifications of new NVIDIA products. These include IC chips in AI, Data Center, Mobile, Automotive, Deep Learning, Graphic Processor, and System on Chip sectors.
Today, we're harnessing the transformative power of AI to define the next era of computing: one where our GPUs , CPUs and networking infrastructure serve as the intelligence behind computers, robots, and autonomous vehicles that understand and navigate the world.
Design, implement, and deploy novel algorithms for spatial understanding, working on problems ranging from SLAM, structure-from-motion, optical flow, scene flow, and object reconstruction to training VLMs on a wide range of spatial reasoning skills.
Develop deep technical understanding of NVIDIA AI, accelerate computing portfolio inclusive of GPU, DPU, CPU, reference architectures, software, licensing models. Understand Lenovo’s product stacks including Data Center, Client, Edge, Networking, and Storage.
Design & Integrate: Collaborate with the network architecture team to review and comment on network designs.
US, USA