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Conduct novel research in AI security and cybersecurity, focusing on securing AI models, agents, systems, and infrastructure. Develop tools and processes to identify and remediate vulnerabilities, investigate adversarial machine learning, publish findings, and collaborate across NVIDIA. Present complex technical results to security, machine learning, and business audiences while contributing to secure software development and AI safety.

Builds secure AI and agentic cybersecurity tooling, transforming research prototypes into production-ready services. Responsibilities include developing backend services, APIs, CLI tools, automation, and integration patterns; defining MVPs for ambiguous security and identity challenges; collaborating across research, product, enterprise security, and platform teams; and applying offensive security and adversarial thinking to address AI-specific risks such as injection, tool misuse, unauthorized access, data exfiltration, and unsafe delegation.

Lead the architecture and implementation of NVIDIA’s large-scale data retrieval platform for foundation-model training. Build web crawling, source discovery, indexing, scheduling, fetching, ingestion, provenance, and policy-enforcement systems. Ensure production reliability, scalability, observability, and cost efficiency while supporting open-web, licensed, partner, code, STEM, and multimodal data. Partner across engineering, research, product, legal, privacy, and governance teams, mentor engineers, and set technical direction.

Lead and grow the Isaac Manipulation engineering team to deliver production-grade robotic manipulation capabilities. Define roadmap, bridge research and product, partner with OEMs and developers, leverage NVIDIA GPUs/CUDA/PyTorch and simulation for sim-to-real learned policies, and drive delivery of manipulation stacks onto physical robots.

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.

Develop and maintain upstream Linux kernel support for NVIDIA GPU virtualization. Build virtualization features in Rust and C, contribute patch series to the Linux kernel, and work across KVM, QEMU, VFIO, PCIe SR-IOV, memory management, and device lifecycle systems. Debug complex host, hypervisor, driver, firmware, performance, and reliability issues while collaborating with maintainers, partners, and distributed engineering teams.

Design, build, and operate core cloud-native infrastructure services for NVIDIA DGX Cloud. Develop scalable, secure microservices and automation for provisioning and lifecycle management, integrate internal and external platforms, and implement observability and security to ensure reliable, global production operations.

The role involves performing data analysis for datacenter applications, using machine learning for GPU systems, and providing insights on trends to enhance workflows.

Build and operate security controls, telemetry, detections, and enforcement for NVIDIA’s large-scale EDA compute, storage, and networking infrastructure across on-premises and multi-cloud environments. Investigate threats, respond to incidents, automate secure configurations and compliance evidence, threat-model infrastructure, and manage security technology lifecycles. The role requires hands-on Linux, networking, programming, infrastructure security, and collaboration with infrastructure and security teams.

Own and evolve Kubernetes networking for GPU superclusters spanning multiple clouds and thousands of nodes. Design and operate CNI data planes, overlay meshes, VPNs, gateways, load balancers, and tunnels. Identify scale limitations, build network validation environments, diagnose distributed networking failures, and partner with cloud providers on topology. Provide technical leadership while using strong Linux networking, systems programming, and large-scale debugging expertise.