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Develop system software and firmware for power management across Tegra automotive, embedded, and data center SoCs. Responsibilities include implementing power policies, debugging complex system issues, collaborating on performance and efficiency strategies, creating validation plans, and analyzing energy consumption. The role requires strong C/C++ and Python skills, system-level software experience, and knowledge of computer architecture, operating systems, and hardware-software interactions.

Develop and deploy scalable AI solutions, distributed training and inference systems, and MLOps pipelines across cloud and NVIDIA platforms. Serve as a technical lead for customers and partners, optimize large-scale workloads for performance and cost, diagnose full-stack infrastructure problems, and create open-source tools and reference architectures. The role requires strong AI/ML lifecycle experience, systems expertise, programming skills, and communication abilities.

Designs, deploys, maintains, and tunes large-scale HPC and AI clusters. Responsibilities include workload scheduling, infrastructure automation, CI/CD pipelines, monitoring, logging, alerting, storage and networking deployment, bottom-up troubleshooting, methodology documentation, and R&D support. The engineer works across hardware, operating systems, GPU computing, virtualization, cloud platforms, and software stacks to deliver performant, reliable self-service infrastructure.

The role involves validating clocking structures in products, developing test plans, automation, and partnering with design teams to ensure high-quality verification of ASIC designs.

Lead product strategy and multi-quarter roadmaps for NVIDIA’s AI Factory software-defined networking stack. Guide upstream development across OVN, OVS, and OVN-Kubernetes; define requirements, priorities, and architecture trade-offs; coordinate dependencies across DPU, fabric, virtualization, and engineering teams; and translate partner and operator needs into product releases, reference deployments, and community strategy.

Own go-to-market strategy and positioning for NVIDIA desktop AI products. Lead cross-functional teams through planning, launch, and post-launch optimization. Coordinate OEM and channel messaging, train regional sales, collaborate with product/sales/marketing, and drive analyst/influencer relations to grow pipeline and sell-through.

Lead product vision, roadmap, and execution for Omniverse rendering, ovrtx, and sensor simulation. Define AI-ready simulation workflows, translate customer needs into product requirements, partner with engineering on rendering and sensor fidelity, prioritize SDKs/APIs and developer tools, and work with customers and partners to drive adoption and validate simulation for perception, robotics, and digital twin use cases.

Lead individual-contributor responsible for designing, coding, and deploying deterministic and stochastic supply network simulations and AI/ML augmentations to forecast long-lead procurement. Audit large datasets, translate outputs into VP-level recommendations, modernize legacy planning into automated high-performance scripts, and partner with supply chain, procurement, finance, and engineering to optimize sourcing and material forecasting.

Lead architecture and implementation of hardware abstraction layers, drivers, runtimes, and data-movement pipelines in Rust. Drive platform bring-up, triage difficult runtime and hardware faults, define long-lived APIs and compatibility practices, establish AI-assisted engineering workflows, and collaborate with hardware, compiler, and operations teams to ensure production-scale reliability and performance.

Conduct fundamental and applied robotics research across perception, planning, control, and learning. Develop algorithms for manipulation and loco-manipulation, integrate methods into real robotic systems and simulators, publish and engage with academia, transfer research to products, collaborate across teams, and mentor interns.