Solutions Architect: Multimodal AI & Research Partnerships

NVIDIA; Greater London; On-site; GBP 90,000 - 125,000; Full time

Job summary

NVIDIA in London seeks a Solutions Architect to partner with academia and research partners, serving as a primary technical contact and driving adoption of NVIDIA technology. You will engage researchers and developers to advance Multimodal AI and Physical AI on multi-node GPU systems, including training and demonstrations.

The role requires direct collaboration with leading labs, ongoing industry trend tracking, and hands-on work across NVIDIA's platforms, with travel as part of the job.

Qualifications

• Graduate degree in a STEM field.
• 5+ years in multimodal world model lifecycle on multi-node GPU systems.
• Strong collaboration and communication with academic stakeholders.
• Analytical, self-motivated with excellent organization in multi-tasked environments.
• Fluent in English and comfortable working in Python.

Responsibilities

• Partner directly with leading research labs, researchers, and university faculty as a technical advisor for joint research at supercomputing scale.
• Identify and accelerate high-impact workloads by integrating NVIDIA frameworks and core software into research projects and disseminate findings.
• Advocate for accelerated computing, Multimodal AI and Physical AI; deliver trainings, workshops, and demonstrations; mentor powerusers.
• Track emerging research trends and convert gaps into prototypical solutions; provide feedback to NVIDIA Engineering.
• Maintain deep domain expertise across GPUs, CPUs, networking, and software within NVIDIA's platform.

Skills

Python

Education

Graduate degree in STEM

PhD in STEM

Tools

CUDA

Job description

NVIDIA in London seeks a Solutions Architect to partner with academia and research partners, serving as a primary technical contact and driving adoption of NVIDIA technology. You will engage researchers and developers to advance Multimodal AI and Physical AI on multi-node GPU systems, including training and demonstrations.

The role requires direct collaboration with leading labs, ongoing industry trend tracking, and hands-on work across NVIDIA's platforms, with travel as part of the job.