Senior Solutions Architect, Generative AI Deployment, AIOps

🕒 il y a 5 mois

🏄 California, Illinois, +2 états de plus – 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 36%

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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

• Partnering with other solution architects, engineering, product and business teams • Understanding their strategies and technical needs and helping define high-value solutions • Dynamically engaging with developers, scientific researchers, and data scientists, gaining experience across a range of technical areas • Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform • Working closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions • Analyzing performance and power efficiency of AI inference workloads on Kubernetes • Some travel to conferences and customers may be required (20%)

🎯 Exigences

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) • 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow • Strong fundamentals in programming, optimizations, and software design, especially in Python • Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments • Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments • Excellent knowledge of the theory and practice of LLM and DL inference • Excellent presentation, communication and collaboration skills

🏖️ Avantages

• equity • benefits

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