Research Scientist – Large Tabular Models (LTMs)

• 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.

• PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field preferred; equivalent research and/or industry experience and demonstrated contributions to advancing state-of-the-art AI models will also be considered.
• 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.
• Experience in structured learning, representation learning, generative modeling, probabilistic modeling, statistical learning, or scalable ML systems is particularly relevant.

• 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.

• Crunch reduces storage and processing costs across enterprise data infrastructure.
• Large Tabular Models unlock predictions and generated data from governed enterprise tables.
• Myelin reduces token and compute overhead for long-running AI agents.

Everything runs inside the customer’s perimeter, so enterprises retain control of their data and the intelligence it creates.

Granica has already processed hundreds of petabytes of enterprise data in production for customers including Snap, Pinterest, Lyft, and ShareChat.

Our research organization is led by Stanford Professor Andrea Montanari.

We operate at the intersection of data infrastructure, AI systems, and applied research, building the efficiency and intelligence layer for enterprise AI.

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

At Granica, you'll help build the next generation of enterprise AI—from exabyte-scale data infrastructure, Large Tabular Models (LTMs), and stateful AI agents. Together, we're creating the infrastructure that enables enterprises to own their data, own the intelligence built on it, and scale both efficiently.

Granica helps enterprises run AI for less, from the data layer to agent execution.