AI Research Solutions Architect — Global Travel

NVIDIA Corporation; United States; Remote; USD 199,000 - 252,000; Full time

Benefits offered by this job

Travel up to 30%

Job summary

NVIDIA Corporation in London is seeking a Solutions Architect to partner with leading research labs and academia, driving adoption of NVIDIA AI and HPC platforms. You will serve as a trusted technical advisor, translating research goals into actionable GPU-accelerated workloads across multi-node systems.

You will collaborate across researchers and engineers, deliver hands-on trainings, and stay at the frontier of large language model workflows, while traveling up to 30% to meet partners and

Qualifications

• Graduate degree in a STEM field from a leading university.
• 5+ years hands-on experience with large language model lifecycles across multi-node systems (training, fine-tuning, inference, serving).
• Strong collaboration and communication skills with academic/research stakeholders.
• Fluent in English (oral and written); proficient in Python.

Responsibilities

• Partner with leading research labs, researchers and university faculty as a trusted technical advisor.
• Identify and accelerate workloads by integrating NVIDIA’s frameworks and core software into research projects.
• Advocate for accelerated computing and Deep Learning; deliver trainings, workshops, lectures, and demonstrations.
• Track emerging research trends and translate gaps into prototypical solutions for NVIDIA Engineering.
• Maintain deep domain expertise across GPUs, CPUs, networking, and software.

Skills

LLM lifecycle

Multi-node systems

Scientific collaboration

Python fluency

Public speaking

Education

Master’s or PhD in STEM

Tools

CUDA & CUDA-X

Megatron Bridge

TensorRT-LLM

Job description

NVIDIA Corporation in London is seeking a Solutions Architect to partner with leading research labs and academia, driving adoption of NVIDIA AI and HPC platforms. You will serve as a trusted technical advisor, translating research goals into actionable GPU-accelerated workloads across multi-node systems.

You will collaborate across researchers and engineers, deliver hands-on trainings, and stay at the frontier of large language model workflows, while traveling up to 30% to meet partners and