Senior Solutions Architect – Generative AI Deployment, AIOps

🕒 il y a 21 jours

🏄 California, Illinois, +3 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 1%

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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

• Partner with other solution architects, engineering, product and business teams to understand strategies and technical needs and define high-value solutions • Engage with developers, scientific researchers, and data scientists across a range of technical areas • Strategically partner with lighthouse customers and industry-specific solution partners targeting NVIDIA’s computing platform • Work with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions • Analyze performance and power efficiency of AI inference workloads on Kubernetes • Serve as a trusted technical advisor on projects and proof-of-concepts focused on inference for Generative AI and Large Language Models • Collaborate with internal teams on performance analysis and modeling of inference software • Travel to conferences and customers as 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 • Prior experience with DL training at scale, deploying or optimizing DL inference in production • Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, TensorRT-LLM • Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design • Familiarity with parallel programming and distributed computing platforms • Some travel to conferences and customers may be required (20%)

🏖️ Avantages

• Equity • Benefits

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