Relational Foundation Model Engineer, Modern Data Stack

Nvidia Corporation in; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA is redefining AI with the Relational Foundation Model team, building a single foundation model that understands relational databases and heterogeneous graphs.

As an engineer on this team, you will design, implement, and evaluate Transformer and graph neural networks, collaborating with researchers to push the boundaries from research to production.

NVIDIA infrastructure powers scalable deployment, and you will contribute to applications such as forecasting, matching, and anomaly detection.

Qualifications

• MS or PhD in Machine Learning, Computer Science, or equivalent experience.
• Proficiency in Python and PyTorch.
• At least 8 years of research experience in designing ML algorithm solutions.
• Practical experience applying Predictive Models in Real World Applications.

Responsibilities

• Collaborate with researchers/engineers to enhance Transformer and GNN-based models to operate over relational schemas and heterogeneous graphs.
• Develop high-impact use cases such as forecasting, entity matching, customer retention and fraud detection using the foundation model.
• Leverage ML knowledge to build scalable and adaptable solutions, pushing the boundaries of what's possible.
• Work across the full ML lifecycle from architecture design/training to post-training optimization and inference acceleration.
• Contribute to the next generation of the Relational Foundation Model.

Skills

Python

PyTorch

Research experience

Predictive models

Education

MS/PhD in ML or CS

Tools

PyTorch

Graph Neural Networks

Job description

Relational Foundation Model Engineer, Modern Data Stack (Finance)

NVIDIA is redefining what is possible with AI, and the Relational Foundation Model team is helping lead that transformation. We are building a unified foundation model that can understand the structure, context, and relationships within relational databases and heterogeneous graphs-opening a new frontier for enterprise AI. As an engineer on this team, you will go beyond adapting existing models: you will design, build, and evaluate novel Transformer and graph neural network architectures that generalize across diverse data schemas. Your work will power meaningful applications, including recommendation systems, demand forecasting, fraud detection, and predictive maintenance.

You will partner with world-class researchers and engineers across the full machine learning lifecycle, from architecture exploration and large-scale training to post-training optimization and high-performance inference. This is an opportunity to turn foundational research into production systems that influence how organizations derive intelligence from complex, connected data. NVIDIA foundation models are optimized for NVIDIA-accelerated infrastructure, providing a strong platform for translating advanced AI research into deployable systems. If you are energized by graph learning, relational reasoning, and building AI that moves beyond single-table benchmarks, we would love to hear from you

What you'll be 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 experience
• 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

Ways to stand out from the crowd:

• Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar

NVIDIA 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!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until August 21, 2026.

This posting is for an existing vacancy.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.