Requirements:

• MS or PhD in Machine Learning, Computer Science, or equivalent program
• 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

Nice to haves:

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

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.

Perks and benefits:

• NVIDIA is widely considered to be one of the technology world’s most desirable employers
• 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!