NVIDIA is redefining what’s possible with AI, and the Relational Foundation Model team is at the forefront of this mission. The team is building a single, unified foundation model that understands the structure and relationships within any relational database or heterogeneous graph, representing a fundamentally new approach to enterprise AI.
Tasks
- Collaborate with researchers and engineers to enhance 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 knowledge in ML and AI to tackle real challenges while contributing to scalable and adaptable solutions.
- Work across the full lifecycle of modern ML systems, including architecture design, training, post-training optimization, and inference acceleration.
- Contribute to the next generation of the Relational Foundation Model.
Requirements
- 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.
- Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar.
- Creative and autonomous working style.
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Über uns
Das Team
The Relational Foundation Model team collaborates closely with researchers and engineers across the full ML lifecycle, contributing to foundational research that ships into production and shapes the modern data stack.