Relational Foundation Model Engineer, Modern Data Stack

Overview

• 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.
• 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.
• 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!.