Leading and coaching a team of Storage Production Engineers, creating a collaborative, inclusive, and learning focused environment. Designing, deploying, and improving large scale storage systems, including distributed storage, parallel file systems, and object storage.
Leading the development of next-gen Scale-up fabric for AI data-centers. Concentrating on collaborative communication and vertical co-development of AI networks alongside hardware, software, and applications.
Lead the canonical DriveOS process architecture, terminology, roles and interfaces across engineering, program management, quality, functional safety, and cybersecurity.
You will own NVIDIA's RL post-training frameworks strategy: where we invest directly, where we partner upstream, and how we prioritize based on customer impact, ecosystem leverage, technical feasibility, and opportunity cost.
Define and prototype AI system architectures spanning optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data.
Manage and mentor a team of Developer Relations Managers to cover AI for science (life sciences, physics, robotics, quantum, climate). Set direction, remove blockers, and build a high-trust, high-performance team.
Designing and building world-class software-defined network infrastructure grounded in EVPN and BGP architectures. Contributing to software development processes with meticulous attention to detail. Performing code reviews to ensure reliable and correct feature implementation.
Set the technical direction for content authenticity AI at NVIDIA — architecting the model and pipeline strategy for detecting synthetic and manipulated media, and making the build-vs-adapt calls that shape multi-year investment.
Lead NDAS execution with major OEMs across the full program lifecycle — from feature definition and technical alignment through vehicle integration, validation, launch, and production ramp — owning the coordinated engineering plan per vehicle line, including requirements,…
Be responsible for the build, implementation, and operational reliability of cluster configurations for NKE tenant workloads across all supported topologies.
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