Granica
Research Scientist — Tabular Data Learning
Granica, San Francisco, California, United States, 94199
Research Scientist – Tabular Data Learning
Join to apply for the
Research Scientist — Tabular Data Learning
role at
Granica
This range is provided by Granica. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $400,000.00/yr - $800,000.00/yr
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.
We eliminate hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Why It Matters Massive data should fuel innovation, not drain budgets. We remove bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
Who We Are
World renowned researchers in compression, information theory, and data systems
Elite engineers from Google, Pure Storage, Cohesity and top cloud teams
Enterprise sellers who turn ROI into seven‑figure wins
Fueled by world‑class investors & customers, we have raised $65M+ from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders.
Our Mission We’re building the default data substrate for AI, a generational company built to endure.
Smarter Infrastructure for the AI Era We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3‑based data lakes, enabling:
60%+ reduction in storage costs and up to 60% lower compute spend
3x faster data processing
20% platform efficiency gains
What You’ll Do
Invent and prototype new algorithms that advance representation learning and compression for structured and tabular data at petabyte scale
Design cost models and adaptive learners that fuse statistical learning theory with systems‑level optimization
Develop novel architectures and approximation schemes that enable efficient inference and training on heterogeneous enterprise data (structured, semi‑structured, unstructured)
Create telemetry‑driven encodings and embeddings that continuously adapt to real‑world data distributions
Partner with Montanari’s research group and Granica’s systems engineers to translate new learning methods into production‑grade services used by customers like Lyft, Pinterest, and Snap
Author world‑class research papers and design docs, mentor peers, and open‑source algorithms where possible
Contribute to the scientific community by publishing results that bridge theory, tabular learning, and scalable infrastructure
What We’re Looking For
PhD in Machine Learning, Statistics, or related mathematical field with focus on representation learning, generalization, or structured data modeling
Publications or applied research in areas such as tabular data learning, feature learning, or multimodal fusion
Strong foundation in optimization, information theory, or statistical learning
Hands‑on experience with deep learning frameworks (PyTorch, JAX, TensorFlow) and Python / Rust for high‑performance prototyping
Track record of validating ideas against large‑scale, real‑world datasets or production systems
Pragmatic researcher who seeks elegant, empirically validated approaches to hard data problems
WHY JOIN GRANICA This is a rare opportunity to build the foundations of learning systems for structured data, working directly with Stanford Prof. Andrea Montanari, one of the leading figures in modern statistical learning theory.
Compensation & Benefits
Competitive salary and equity
Premium healthcare, vision, and dental
Unlimited PTO + quarterly recharge days
Stipends for learning, publishing, or open‑source engagement
Equal Opportunity Granica is an equal opportunity employer. We’re committed to building a diverse, inclusive team and encourage candidates from all backgrounds to apply.
#J-18808-Ljbffr
Research Scientist — Tabular Data Learning
role at
Granica
This range is provided by Granica. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $400,000.00/yr - $800,000.00/yr
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.
We eliminate hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Why It Matters Massive data should fuel innovation, not drain budgets. We remove bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
Who We Are
World renowned researchers in compression, information theory, and data systems
Elite engineers from Google, Pure Storage, Cohesity and top cloud teams
Enterprise sellers who turn ROI into seven‑figure wins
Fueled by world‑class investors & customers, we have raised $65M+ from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders.
Our Mission We’re building the default data substrate for AI, a generational company built to endure.
Smarter Infrastructure for the AI Era We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3‑based data lakes, enabling:
60%+ reduction in storage costs and up to 60% lower compute spend
3x faster data processing
20% platform efficiency gains
What You’ll Do
Invent and prototype new algorithms that advance representation learning and compression for structured and tabular data at petabyte scale
Design cost models and adaptive learners that fuse statistical learning theory with systems‑level optimization
Develop novel architectures and approximation schemes that enable efficient inference and training on heterogeneous enterprise data (structured, semi‑structured, unstructured)
Create telemetry‑driven encodings and embeddings that continuously adapt to real‑world data distributions
Partner with Montanari’s research group and Granica’s systems engineers to translate new learning methods into production‑grade services used by customers like Lyft, Pinterest, and Snap
Author world‑class research papers and design docs, mentor peers, and open‑source algorithms where possible
Contribute to the scientific community by publishing results that bridge theory, tabular learning, and scalable infrastructure
What We’re Looking For
PhD in Machine Learning, Statistics, or related mathematical field with focus on representation learning, generalization, or structured data modeling
Publications or applied research in areas such as tabular data learning, feature learning, or multimodal fusion
Strong foundation in optimization, information theory, or statistical learning
Hands‑on experience with deep learning frameworks (PyTorch, JAX, TensorFlow) and Python / Rust for high‑performance prototyping
Track record of validating ideas against large‑scale, real‑world datasets or production systems
Pragmatic researcher who seeks elegant, empirically validated approaches to hard data problems
WHY JOIN GRANICA This is a rare opportunity to build the foundations of learning systems for structured data, working directly with Stanford Prof. Andrea Montanari, one of the leading figures in modern statistical learning theory.
Compensation & Benefits
Competitive salary and equity
Premium healthcare, vision, and dental
Unlimited PTO + quarterly recharge days
Stipends for learning, publishing, or open‑source engagement
Equal Opportunity Granica is an equal opportunity employer. We’re committed to building a diverse, inclusive team and encourage candidates from all backgrounds to apply.
#J-18808-Ljbffr