Senior Solutions Architect, Higher Education and Research in London

Senior Solutions Architect, Higher Education and Research in London

London Full-Time 75600 - 92400 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Partner with leading researchers to drive innovative AI projects and accelerate computing solutions.
  • Company: Join NVIDIA, a pioneer in computer graphics and AI technology.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic role with travel opportunities and a supportive, collaborative environment.
  • Why this job: Make a real impact in academia and research while working with cutting-edge technology.
  • Qualifications: Graduate degree in STEM, 5+ years in multimodal AI, strong communication skills.

The predicted salary is between 75600 - 92400 £ per year.

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 Multimodal AI and Physical AI with expertise in accelerated computing and architecture.

What you will be doing:

  • 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, robotics, Multimodal AI and Physical AI, 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 offerings 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.

What we need to see:

  • A graduate degree from a leading university in a STEM related discipline.
  • 5+ years in the multimodal and world model lifecycle on multi-node GPU systems: video and image data curation at scale, pre-training and post-training, evaluation, and efficient inference.
  • 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.

Ways to stand out from the crowd:

  • A PhD from a leading university in a STEM related discipline, with 3+ years of research in the domain.
  • 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 stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec for neural reconstruction, TensorRT and NIM for deployment, and domain frameworks such as MONAI for medical imaging.

As a Solutions Architect, there is travel involved, as often the best way to figure things out is a face-to-face meeting, but the job is not life on the road. We make heavy use of conferencing tools, and you are empowered to figure out how to get the job done and do what it takes to make our customers successful.

Senior Solutions Architect, Higher Education and Research in London employer: Nvidia

NVIDIA is a leading innovator in the tech industry, renowned for its commitment to fostering a diverse and inclusive work environment where creativity thrives. As an AI Natives Sales Account Manager, you'll benefit from competitive salaries, comprehensive benefits, and unparalleled opportunities for professional growth while working at the forefront of AI technology in the UK. Join us to make a meaningful impact and be part of a team that values your contributions and encourages innovation.

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Contact Details:

Nvidia Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Solutions Architect, Higher Education and Research in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Nvidia or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Nvidia.

Tap into Online Developer Communities

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We think you need these skills to ace Senior Solutions Architect, Higher Education and Research in London

Multimodal AI
Physical AI
Accelerated Computing
GPU Systems
Python
Collaboration Skills
Communication Skills

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Nvidia.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Nvidia and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Nvidia

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Nvidia uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.