Research Scientist – Large Tabular Models (LTMs)

About the Company

At Granica, we're building Large Tabular Models (LTMs)—foundation models that learn natively from structured and relational enterprise data. Our research is led by Prof. Andrea Montanari (Stanford) and focuses on building generative AI that learns efficiently from tabular data.

Responsibilities

• Develop new machine learning algorithms for Large Tabular Models
• Research methods for selecting, augmenting, and compressing training data without losing information
• Build representation learning techniques for structured and relational datasets
• Prototype and evaluate new approaches for generative modeling over enterprise data
• Design rigorous experiments and benchmarks to measure progress
• Collaborate closely with Prof. Andrea Montanari and Granica's research team to translate research into production systems

Requirements

• PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field
• Strong research record in machine learning
• Experience developing new models or learning algorithms
• Hands-on experience with PyTorch or JAX
• Strong programming skills in Python
• Ability to turn research ideas into working systems

Preferred Qualifications

• Experience in structured learning, representation learning, generative modeling, probabilistic modeling, statistical learning, or scalable ML systems
• Research on tabular, relational, or graph data
• Experience with diffusion or other generative modeling approaches
• Publications at NeurIPS, ICML, ICLR, COLT, KDD, or related venues
• Open-source or production ML systems experience

Benefits

• Competitive salary, meaningful equity, and performance bonus
• 401(k) with company match
• Comprehensive health coverage
• Unlimited PTO
• Daily catered meals in the Mountain View office
• Support for research, publication, and conference participation