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NVIDIA

Relational Foundation Model Engineer, Modern Data Stack

United Kingdom
Posted 1 day ago
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Our Work at NVIDIA

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join us!

NVIDIA is redefining what’s possible with AI, and our Relational Foundation Model team is at the forefront of that mission. We’re building a single, unified foundation model that understands the structure and relationships within any relational database or heterogeneous graph — a fundamentally new approach to enterprise AI. As an engineer on this team, you won’t just be fine-tuning existing models; you’ll be designing and experimenting with novel Transformer and GNN architectures that generalize across diverse relational schemas. Your work will directly impact real-world applications spanning recommendation systems, demand forecasting, fraud detection, and predictive maintenance — all powered by one extensible model. You’ll collaborate closely with researchers and engineers across the full ML lifecycle, from architecture exploration and large-scale training to post-training optimization and inference acceleration. This is a rare opportunity to contribute to foundational research that ships into production and shapes the modern data stack. If you’re excited about graph learning, relational reasoning, and building AI systems that go far beyond single-table benchmarks, this is the team for you.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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What You’ll Be Doing

  • Collaborate with researchers/engineers to enhance our Transformer and GNN-based models to operate seamlessly over any relational schema and heterogeneous graph.
  • Gain hands-on experience with high-impact use cases such as forecasting, entity matching, customer retention and fraud detection – all built on top of a single, extensible foundation model.
  • Leverage your knowledge in ML and AI to tackle real challenges while contributing to scalable and adaptable solutions that push the boundaries of what’s possible.
  • Work may span the full lifecycle of modern ML systems: from architecture design/training to post-training optimization and inference acceleration.
  • You will contribute to our next generation of the Relational Foundation Model.

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What We Need To See

  • MS or PhD in Machine Learning, Computer Science, or equivalent program
  • Proficiency in Python and deep learning frameworks, such as PyTorch
  • At least 8 years of research experience in designing ML algorithm solutions
  • Practical experience in using Predictive Models in Real World Applications

Ways To Stand Out From The Crowd

  • Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

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Skills

Machine Learning
Deep Learning
Python
PyTorch
Graph Learning
Predictive Models
Architecture Design
Optimization
Inference Acceleration
Entity Matching
Customer Retention
Fraud Detection
Forecasting
Relational Reasoning
Transformer Architectures
GNN Architectures

Location

United Kingdom

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