We are now looking for a Solution Architect - Deep Learning based in Israel. The individual will collaborate with brand-new Agentic and Physical AI tools alongside Machine learning, Deep Learning, and Data analytics to improve workflows and develop groundbreaking solutions. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most dedicated individuals in the world working for us. If you’re creative and autonomous, we want to hear from you!
What You’ll Be Doing:
Responsibilities
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Assisting field business development in guiding the customer through the sales process for GPU Computing products, owning the technical relationship and assisting the customer in building innovative solutions based on NVIDIA technology.
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Be a motivating leader in integrating NVIDIA technology into HPC architectures to support scientific and engineering applications.
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Be an internal champion for Deep Learning and Data Science among the NVIDIA technical community.
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Develop demo solutions and showcase to the AI ecosystem.
What We Need To See:
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B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience
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5+ years of experience in software development or extensive data analytics, CUDA experience highly desirable.
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Experience working with modern Deep Learning software architecture and frameworks including PyTorch, VLLM, Triton
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Proven Exposure to GPU technology and CUDA programming
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Demonstrable experience in strategy, research, communications.
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Capable of working in a constantly evolving environment without losing focus.
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Committed with strong analytical and problem solving skills.
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Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.
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Direct experience participating in communities (expertly or as highly engaged developer).
Ways To Stand Out From The Crowd:
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Technical knowledge of developer digital platforms and their trends.
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Experienced working with containers, Kubernetes and MLoPS tools