Relational Foundation Model Intern: Transformers & GNNs

NVIDIA Corporation; France; Sur place; EUR 45 000 - 65 000; Plein temps

Résumé du poste

NVIDIA Corporation in France is seeking a graduate student in ML/CS to contribute to cutting-edge research on Transformer and Graph Neural Network models, collaborating with researchers and engineers.

You will work across the full ML lifecycle, from design and training to deployment and inference, focusing on scalable solutions for real-world AI tasks such as forecasting, entity matching, or fraud detection on an extensible foundation model.

Qualifications

• Pursuing MS or PhD in Machine Learning, Computer Science, or equivalent program area.
• Proficiency in Python and deep learning frameworks, such as PyTorch.
• Coursework or research experience in crafting ML algorithm solutions.

Responsabilités

• Collaborate with researchers/engineers to enhance Transformer and GNN-based models over relational schemas and heterogeneous graphs.
• Gain hands-on experience with forecasting, entity matching, customer retention and fraud detection on a scalable foundation model.
• Apply ML/AI knowledge to address real challenges and develop adaptable solutions.
• Work across the full lifecycle of ML systems from design/training to post-training optimization and inference.

Connaissances

Python

PyTorch

ML research

Formation

MS/PhD in ML or CS (pursuing)

Outils

PyTorch

Description du poste

NVIDIA Corporation in France is seeking a graduate student in ML/CS to contribute to cutting-edge research on Transformer and Graph Neural Network models, collaborating with researchers and engineers.

You will work across the full ML lifecycle, from design and training to deployment and inference, focusing on scalable solutions for real-world AI tasks such as forecasting, entity matching, or fraud detection on an extensible foundation model.