Senior Solutions Architect, Higher Education and Research - Open Models and LLM

Nvidia
Greater London, UK
7 days ago
Apply on nvidia.wd5.myworkdayjobs.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Languages
English

Tech stack

Artificial Intelligence Nvidia CUDA Microprocessors Python (Programming Language) Graphics Processing Unit (GPU) Large Language Models Deep Learning Machine Learning Operations TensorRT Nim (Programming Language)

Job description

  • Partner directly with leading research labs, researchers, and university faculty as a trusted technical advisor: develop a keen understanding of their scientific goals and drive joint research projects at supercomputing scale.
  • Identify and accelerate high-impact workloads by integrating NVIDIA’s frameworks, libraries, and core software stack into research projects, and help researchers amplify their impact through publications, conference presentations, and technical content.
  • Advocate for accelerated computing and Deep Learning, and deliver hands-on trainings, workshops, lectures, and demonstrations across NVIDIA’s platforms, and mentor power users to become NVIDIA champions.
  • Track emerging research trends and turn gaps between researcher needs and NVIDIA’s o erings into prototypical solutions and direct feedback to NVIDIA Engineering.
  • Maintain deep expertise in your domain while staying versatile across NVIDIA’s full platform: GPUs, CPUs, networking, and software

Requirements

  • A graduate degree from a leading university in a STEM related discipline.
  • 5+ years of hands-on experience running the large language model lifecycle across multi-node systems: training, fine-tuning, inference, serving, and/or agentic workflows.
  • Strong collaboration and communication skills, with the ability to build relationships with academic and research stakeholders, and to communicate complex ideas clearly to both expert and non-expert audiences.
  • Action oriented, analytical, self-motivated, and a passionate learner, with excellent organization skills to work in a heavily multi-tasked environment.
  • Fluent in English, both oral and written, and comfortable working in Python., * A PhD from a leading university in a STEM related discipline, with 3+ years of research on large language models or foundation models and their applications.
  • A track record of thought leadership: high-impact publications, talks at academic conferences and workshops, as well as good understanding of scientific policy engagement, grant processes, or national/European research program structures.
  • Experience with NVIDIA’s AI software stack, powered by CUDA and CUDA-X libraries, e.g. NVIDIA AI Enterprise, NeMo Framework, Megatron Bridge, NIM, TensorRT-LLM, Dynamo, NeMo Agent Toolkit, and Triton Inference Server, as well as the Nemotron open-model methodology.

About the company

NVIDIA has been redefining computer graphics and accelerated computing for three decades. Today, we are tapping into the unlimited potential of AI to define the next era of computing. Doing what has never been done before takes vision, innovation, and exceptional talent. As an NVIDIAN, you will be immersed in a diverse, supportive environment where everyone is encouraged to do their best work and make a lasting impact on the world. We are looking for a Solutions Architect in the Greater London area to work with academia and research partners. Solutions Architects are the primary technical contacts for our customers and engage deeply with researchers and application developers to drive the adoption of NVIDIA technology. We seek an individual who combines an intricate understanding of modern AI and HPC research workloads with expertise in accelerated computing and architecture.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on nvidia.wd5.myworkdayjobs.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

6:21 min

Previewing upcoming hardware acceleration capabilities for Python environments

Chris Heilmann +2 · LIVE

4:52 min

Essential phases in building and refining language models

Anshul Jindal Anshul Jindal +1 · World Congress 2025

2:15 min

Open-source community and machine learning frameworks

Gian Marco Iodice Gian Marco Iodice · World Congress 2025

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · World Congress 2026 Europe

3:30 min

Transitioning from CUDA software architect to user

Stephen Jones · Coffee With Developers

Videos

See all

Related articles

See all