Research Scientist – Large Tabular Models (LTMs)

What You'll Work On

• 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.

What We're Looking For

• 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.
• Able to turn research ideas into working systems.
• Experience in structured learning, representation learning, generative modeling, probabilistic modeling, statistical learning, or scalable ML systems is particularly relevant.
• Bonus: 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.

Compensation & Benefits

• Competitive salary, meaningful equity, and performance bonus for top performers.
• 401(k) with company match, comprehensive health coverage, and unlimited PT.
• Daily catered meals in our Mountain View office.
• Support for research, publication, and conference participation.