Solutions Architect, CSP GTM

🔥 12 hours ago

🇩🇪 Germany – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 11%

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Develop and demonstrate Physical AI solutions based on Hyperscalers and NVIDIA’s software and hardware technologies • Work directly with key customers and Hyperscaler partners to understand challenges and provide solutions based on NVIDIA products • Perform in-depth analysis and optimization for GPU-accelerated systems using NVIDIA software platforms • Support optimization of training and inference pipelines • Partner with Engineering, Product and Sales teams to understand developer challenges and plan suitable solutions • Enable product feature development and growth through customer feedback and proof-of-concept evaluations • Build industry expertise and contribute to integrating NVIDIA technology into Enterprise Computing architectures • Drive relationships with technical executives and managers to evangelize accelerated computing and Generative AI • Engage with developers, researchers, data scientists, IT managers and senior leaders

🎯 Requirements

• MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields • 5+ years in Solutions Architecture/Engineering in AI-related domains • Excellent ability to listen, both verbal and written communication skills, and comfort presenting technical solutions in English • Expertise with Physical AI solutions on Hyperscaler's infrastructure • Proven academic and/or industry experience in machine learning, deep learning and/or data science • Ability to work with multiple levels and teams across Engineering, Product, Sales and Marketing • Self-starter with interest in growth, passion for continuous learning and sharing findings across the team • Background with Physical AI solutions and offerings using Hyperscaler platforms • Experience running and optimizing large-scale distributed deep learning training and optimizing inference pipelines • Understanding of inferencing techniques, including model compression, model compilation or model serving • Background working with larger transformer-based architectures • Expertise in DevOps technologies such as Docker, Kubernetes, Singularity, etc.

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