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As a senior software engineer at NVIDIA, you will design and build tools for performance analysis of AI workloads, lead automation efforts, and enhance workflows for engineers.

Apply machine learning to real-time graphics and interactive experiences: develop models from latest research, prototype applications, collaborate across teams, and productize neural graphics features for gaming and visualization.

Lead signal and power integrity analysis for high-speed systems: develop SI solutions, run 3D/2.5D/2D EM and system-level simulations, correlate models with lab measurements, create board/substrate SI guidelines, automate simulations and data visualization, and collaborate across package/PCB/ASIC design teams.

Create and deliver developer-focused technical content and workshops that teach CUDA and NVIDIA GPU technologies. Evaluate new CUDA features, produce tutorials and blog posts, capture developer feedback to inform product decisions, and collaborate across product, engineering, and marketing teams to drive developer adoption.

Lead development and deployment of scalable ML, prescriptive analytics, and constrained-optimization models for real-time routing, scheduling, capacity allocation, and personalization in cloud gaming. Build data ingestion and processing frameworks, improve data quality, analyze patterns with supervised/unsupervised methods, and collaborate cross-functionally to deliver prescriptive pipelines and actionable recommendations that optimize latency, utilization, and retention.

Lead research and development of algorithms and systems for robotic manipulation and loco-manipulation; integrate methods into real robot systems; co-lead multi-person projects; publish and engage with the academic community; transfer research into NVIDIA products; and mentor interns and junior researchers/engineers.

Lead architecture and implementation of scalable, distributed NGC Cloud services. Provide technical leadership across the platform, drive operational excellence for secrets and artifact management, influence architecture and technical direction, and enable teams to deliver secure, scalable cloud solutions at global scale.

Architect and demonstrate simulation workflows using DSX Sim and Omniverse libraries to help partners and customers build, validate, optimize, and operationalize AI factory digital twins. Drive integration of Omniverse libraries, develop reference architectures, prototypes, benchmarks, and sample workflows, and coordinate with sales, product engineering, and partners to resolve blockers and advance adoption.

Own design, automation, and lifecycle of Kubernetes platform for global network infrastructure. Build production-quality tooling for cluster provisioning, upgrades, GitOps delivery, observability, and recovery. Provide production support and incident response for network services on the platform, drive root-cause analysis, and establish platform standards and runbooks.

Lead foundry supplier management from NPI to HVM, optimize device performance and yield, perform WAT and qualification, manage SPC and DPPM reduction, collaborate cross-functionally on performance/power/reliability goals, standardize and automate data/procedures, and develop solutions to improve yield projections and problem resolution.