Relational Foundation Model Engineer, Modern Data Stack

What you'll do

• Develop Transformer- and GNN-based models for relational schemas and heterogeneous graphs.
• Collaborate across the machine-learning lifecycle, from architecture design and large-scale training to post-training optimization and inference acceleration.
• Contribute to a foundation model supporting applications such as forecasting, entity matching, customer retention, and fraud detection.

What they ask for

• MS or PhD in Machine Learning or Computer Science, or equivalent experience.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• At least 8 years of research experience designing ML algorithm solutions.
• Practical experience using predictive models in real-world applications.

Nice to have

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

Pay

184,000 USD - 287,500 USD base salary for Level 4; 224,000 USD - 356,500 USD base salary for Level 5.

Tools

Python, PyTorch, Transformer, GNN

AI focus

Build and evaluate a relational foundation model using Transformer and graph neural network architectures; work includes training, post-training optimization, and inference acceleration.