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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Relational Foundation Model Engineer - **Company:** Nvidia - **Location:** München, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Relational Databases, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Recommender Systems, Large Language Models, Deep Learning, Information Technology, Machine Learning Operations - **Published:** August 23, 2026 - **Apply:** https://www.jobfinder.de/job/relational-foundation-model-engineer-modern-data-stack/ ## About the Role 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 programProficiency in Python and deep learning frameworks, such as PyTorchAt least 8 years of research experience in designing ML algorithm solutionsPractical experience in using Predictive Models in Real World ApplicationsWays to stand out from the crowd:Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similarNVIDIA 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!SummaryLocation: Germany, Munich; UK, Remote; Switzerland, Remote; Germany, Remote; France, RemoteType: Full time ## Description 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 ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [100 million days in Vienna: A story of APIs & AI in tourism.](https://www.wearedevelopers.com/videos/93-100-million-days-in-vienna-a-story-of-apis-ai-in-tourism) - [Nemotron: NVIDIA's open model strategy for developers](https://www.wearedevelopers.com/videos/100064-nemotron-nvidia-s-open-model-strategy-for-developers) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)