Senior Solutions Architect, AI Factory

NVIDIA NVIDIA · Semiconductors · Munich, Germany

NVIDIA is seeking a Senior Solutions Architect with expertise in AI Supercomputing to support academic and commercial groups using NVIDIA products for deep learning, data analytics, and scientific simulation. The role involves understanding customer needs, developing solutions, demonstrating workflows, and communicating requirements to NVIDIA Engineering. Requires 3+ years of Deep Learning research experience, experience with LLM training and adaptation, and familiarity with DL frameworks and Generative AI.

What you'd actually do

  1. Be an inspiring leader on integrating NVIDIA technology into IT infrastructures focusing on performance at scale, reliability, manageability, real-time monitoring, etc.
  2. Interact with end-users in academia and industry, develop a keen understanding of their goals and needs, define and deliver high-value solutions that meet these needs.
  3. Identify gaps and propose/develop prototypical solutions.
  4. Demonstrate accelerated computing and AI workflows, deliver trainings using NVIDIA GPUs and software for AI research, groom power users to be NVIDIA champions e.g. as DLI Ambassadors.
  5. Communicate customer requirements to NVIDIA Engineering to foster product improvements.

Skills

Required

  • 3+ years of research experience in Deep Learning
  • Experience with Large Language Models (LLM) training and adaptation
  • graduate degree from a leading university in a STEM related field
  • Significant experience in High-Performance Computing or Deep Learning
  • Strong collaboration and social skills
  • ability to communicate effectively with customers, and across organizations (Engineering, Sales, Support)
  • Experience with DL frameworks, multi-GPU computing, Generative AI
  • Fluent in English both oral and written

Nice to have

  • Experience with data curation pipeline at scale, data formats, filtering, cleaning
  • Experience working with EuroHPC-class supercomputers or tier-1 clouds at scale
  • Skilled at profiling, analyzing and optimizing code
  • Understanding of HPC system architecture inc. distributed computing, networking, parallel filesystems, cluster operations, workload schedulers, etc.
  • Experience working with NVIDIA technologies inc. NVAIE, NeMo, CUDA, NIM, etc.

What the JD emphasized

  • track record of scientific publications
  • Large Language Models (LLM) training and adaptation

Other signals

  • customer-facing technical role
  • integrating NVIDIA technology into IT infrastructures
  • demonstrate accelerated computing and AI workflows
  • LLM training and adaptation