Research Scientist – Diffusion Models

Granica Computing, Inc.; San Francisco (CA); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive health coverage

Unlimited PTO

Daily catered meals at the office

Support for research and conferences

Job summary

Granica Computing, Inc. is seeking a talented researcher to develop novel diffusion models and generative learning algorithms. The role involves collaborating with leading experts and creating techniques for Large Tabular Models. Ideal candidates will have a PhD in a relevant field and a strong background in generative machine learning.

Enjoy competitive salary, equity, unlimited PTO, and other generous benefits while contributing to cutting-edge AI developments at Granica.

Qualifications

• PhD in a relevant field
• Strong research record in generative machine learning
• Experience developing new generative models or learning algorithms

Responsibilities

• Develop novel diffusion models and generative learning algorithms
• Research new representation learning techniques for Large Tabular Models
• Collaborate closely with the research team

Skills

Generative machine learning

Research record

Hands-on experience with PyTorch

Strong programming skills in Python

Experience with diffusion models

Education

PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field

Tools

PyTorch

JAX

Job description

Overview

Diffusion models have transformed image, video, and multimodal AI.

We're applying those ideas to one of the next frontiers in machine learning.

At Granica, we're building Large Tabular Models (LTMs)—foundation models designed to learn natively from enterprise data. Realizing that vision requires new generative modeling techniques capable of learning from structured information at scale.

Our research is led by Prof. Andrea Montanari (Stanford) and explores a fundamental question:

How can diffusion models enable the next generation of AI for enterprise data?

If you're excited about inventing new generative learning algorithms and applying them to entirely new domains, we'd love to talk.

What You’ll Work On

• 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.

What We’re Looking For

• 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.

• Experience with diffusion models, score-based generative modeling, representation learning, probabilistic modeling, or scalable ML systems is particularly relevant.

Bonus

• 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.

Compensation & Benefits

• 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.