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Relational Foundation Model Intern, Modern Data Stack – 2027

NVIDIA· Intern
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Hybrid (Germany), Hybrid (France)internPosted 1w ago

About the role

Internship focused on enhancing Transformer and GNN-based models to operate over relational schemas and heterogeneous graphs, with hands-on experience across ML system lifecycle from architecture to inference acceleration, leveraging a single extensible foundation model.

Responsibilities

  • Collaborate with researchers/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.
  • Apply knowledge in ML and AI to address 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.

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

Skills

Required:PythonDeep learning frameworksML algorithm development
Last updated Oct 16, 2026. Interested? Apply on the company site.

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