Research Scientist

About the Company

At Granica, we're building Large Tabular Models (LTMs)—foundation models designed to learn natively from enterprise data. Our research is led by Prof. Andrea Montanari (Stanford) and explores how diffusion models can enable the next generation of AI for enterprise data.

Responsibilities

• Develop novel diffusion models and generative learning algorithms
• Research new representation learning techniques for Large Tabular Models
• Design efficient training methods for large-scale generative models
• Prototype and evaluate new generative modeling approaches
• Design rigorous experiments and benchmarks to measure model quality and efficiency
• 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 generative machine learning
• Experience developing new generative 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 with diffusion models, score-based generative modeling, representation learning, probabilistic modeling, or scalable ML systems
• Research applying diffusion models beyond traditional vision tasks
• Publications at NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, 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 our Mountain View office
• Support for research, publication, and conference participation