Senior Solutions Architect, Generative AI

🕒 il y a 1 mois

🏄 California, Washington – Distant

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💵 $184 000 - $287 500 / an

⏰ Temps Plein

🟠 Senior

💻 Ingénieur Solutions

🦅 Parrain de Visa H1B

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👻 Score fantôme 7%

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🗣️🇺🇸🇬🇧 Anglais requis

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Logo of NVIDIA

NVIDIA

10 000+ employés

Fondée en 1993

🏥 Santé

🏭 Fabrication

🤖 Intelligence artificielle

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

Description

• Collaborating closely with customers to maximize GPU utilization and end-to-end workload throughput while improving infrastructure reliability and reducing infrastructure costs. • Designing and optimizing large-scale AI clusters across GPU compute, high-performance networking, storage, workload scheduling, orchestration, and observability. • Profiling distributed training and inference workloads to identify bottlenecks across GPUs, CPUs, memory, network fabrics, storage systems, and software stack. • Diagnosing complex infrastructure and distributed systems issues spanning InfiniBand and RoCE fabrics, cloud interconnects, RDMA, NCCL, NVLink, and NVSwitch. • Leading proof-of-concepts and performance studies for large-scale AI infrastructure, developing benchmarking tools, automation, runbooks, and technical collateral as needed. • Partnering with NVIDIA’s engineering, product, and sales teams to secure design wins and drive innovative solutions based on customer requirements and field feedback.

🎯 Exigences

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or another Engineering field, or equivalent experience. • 6+ years of experience in AI infrastructure, systems engineering, high-performance computing, networking, site reliability engineering, or a related technical role. • Deep understanding of Linux systems, distributed computing, GPU architectures, and the hardware and software components of large-scale AI clusters. • Hands-on experience designing, deploying, operating, or troubleshooting high-performance GPU networks in on-premises or cloud environments using technologies such as InfiniBand, RoCE, or GPUDirect RDMA. • Experience debugging NCCL communication and distributed collective performance, including topology, transport, congestion, routing, and host-level configuration issues. • Experience profiling AI workloads and identifying performance bottlenecks across compute, networking, storage, and orchestration layers. • Experience with cluster schedulers and orchestration platforms such as Kubernetes and Slurm, along with containers and production monitoring systems. • Proficiency with Python, shell scripting, or similar languages for infrastructure automation, benchmarking, and systems troubleshooting.

🏖️ Avantages

• equity • generous benefits package

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