Relational Foundation Model Intern, Modern Data Stack – 2027
Core
Enhance Transformer and GNN-based models to operate over relational schemas and heterogeneous graphs for high-impact use cases like forecasting, entity matching, customer retention, and fraud detection.
Role type
Intern, research IC (relational foundation models)
Builds
Scalable and adaptable foundation models for modern data stacks
Domain
AI/ML, Graph Neural Networks, Relational Databases
Deliverable
production ML models
Required skills
Python, PyTorch, Machine Learning algorithms, Graph-based machine learning
Preferred skills
Publications at NeurIPS, ICLR, ICML
Technologies
PyTorch, Transformer models, GNNs
Responsibilities
Collaborate with researchers/engineers to enhance models; Apply ML/AI knowledge to address real challenges; Work on full lifecycle of modern ML systems from architecture design to inference acceleration.
