Senior Product Architect, Storage

🕒 vor 3 Monaten

🏄 California – Remote

🏄 California – Remote

💵 $224.000 - $356.500 / Jahr

⏰ Vollzeit

🟠 Senior

🏛️ Architekt

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NVIDIA

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10.000+ Mitarbeiter

Gegründet 1993

🤖 Künstliche Intelligenz

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA ist ein führendes Technologieunternehmen mit Spezialisierung auf beschleunigtes Computing und Künstliche Intelligenz (AI). NVIDIA treibt Fortschritte bei Grafikprozessoren (GPUs), Cloud Computing, Rechenzentren und Virtual Reality voran und fokussiert dabei Branchen wie Gaming, Automotive, Gesundheitswesen und Robotik. Innovationen des Unternehmens wie NVIDIA Omniverse transformieren traditionelle digitale Prozesse, indem sie hochrealistische Simulationen und Rendering-Aufgaben ermöglichen. Die Anwendungen erstrecken sich über zahlreiche Branchen – von autonomen Fahrzeugen mit NVIDIA DRIVE über Gesundheitslösungen mit NVIDIA Clara bis hin zu AI-gestützten Analysen und Workflows.

Beschreibung

• Architect end-to-end reference architectures for disaggregated inference (aligned with NVIDIA Dynamo), large-scale foundation model training, and agentic AI pipelines — co-developed with storage and ecosystem partners. • Design and validate storage-optimized AI infrastructure, including KV Cache tiering strategies, checkpoint acceleration, and high-throughput dataset pipelines that leverage RDMA and NVMeoF fabrics. • Define system-level architectures spanning Rubin graphics processors, Vera central processing units, BlueField data processing units, NVLink interconnects, and Spectrum-X Ethernet to improve efficiency across the full AI lifecycle. • Develop and publish reference architectures, whitepapers, and deployment guides for the NVIDIA AI Data Platform and partner-integrated solutions. • Drive prototyping, benchmarking, and performance validation of AI infrastructure at scale - diagnosing bottlenecks across compute, networking, and storage layers. • Leverage DOCA to architect DPU-offloaded data services including storage acceleration, telemetry, security enforcement, and network virtualization. • Collaborate with RAG and autonomous AI teams to build retrieval-optimized storage architectures, including vector database integration, low-latency object access patterns, and inference-aware caching. • Partner with customers and collaborators in the ecosystem to co-innovate, deliver proof-of-concepts (POCs) and MVPs that demonstrate end-to-end AI platform performance leadership.

🎯 Anforderungen

• 12+ years of experience architecting datacenter-scale AI, HPC, or storage infrastructure as a Principal Architect, Solutions Architect, Principal Engineer, or equivalent. • Bachelors in Computer Science or related field (or equivalent experience). • Deep expertise in AI infrastructure build, including disaggregated inference architectures, LLM training pipelines, and autonomous AI system patterns. • Hands-on experience with RDMA (RoCEv2/InfiniBand), high-performance storage protocols (NVMeoF, GPFS, Lustre, or S3-compatible object storage), and low-latency fabric design. • Strong understanding of KV Cache management strategies, including tiered memory/storage hierarchies for inference optimization. • Familiarity with Retrieval-Augmented Generation (RAG) architectures and the storage, indexing, and retrieval patterns they demand at scale. • Experience with NVIDIA DOCA or equivalent DPU/SmartNIC programming frameworks for offloading data plane and storage services. • Proven foundation in networking: Spectrum-X Ethernet, InfiniBand, NVLink Switch fabrics, congestion control, and datacenter topologies.

🏖️ Vorteile

• Equity • Benefits