About Granica
Granica is an AI research and infrastructure company focused on reliable, steerable representations for enterprise data.
We earn trust through Crunch, a policy-driven health layer that keeps large tabular datasets efficient, reliable, and reversible. On this foundation, we’re building Large Tabular Models—systems that learn cross-column and relational structure to deliver trustworthy answers and automation with built-in provenance and governance.
Research Product Manager — Structured AI Systems & Economic Extraction
Location: Downtown Mountain View, CA (office-based, five days a week)
Team: Research & Applied Systems
The Mission
Granica’s Research team is advancing foundational work in:
Tabular data learning and large tabular models
Structured and relational representation learning
Compression-aware and efficiency-driven AI
Hybrid symbolic, relational, and neural systems
The intersection of information theory, learning theory, and large-scale systems
These efforts are tightly coupled with real production systems operating over petabytes of enterprise data.
The mission of the Research Product Manager is to ensure this work moves forward coherently, efficiently, and at scale—connecting people, ideas, compute, and systems so that breakthrough research becomes durable capability.
This role is not program management.
It is for someone who can:
Understand how large AI models are trained, deployed, and maintained in production systems
Translate foundational modeling advances into economically valuable infrastructure
Shape both the technical execution path and the economic strategy behind it
What This Role Actually Owns
1️⃣ Productionization of Structured AI Models
Work with Research and Systems teams to:
Design how large tabular models are trained on Parquet / Iceberg / Delta data
Define training infra requirements (data pipelines, distributed training, evaluation loops)
Define inference architecture (batch vs streaming, embedding materialization, retrieval)
Define maintenance loops (retraining cadence, data drift detection, schema evolution)
Understand storage/compute trade-offs in real systems
You must be able to reason about:
Data layout
Compute scheduling
Model lifecycle
Infrastructure bottlenecks
Evaluation pipelines
2️⃣ Economic Value Extraction
Help define:
Who the buyer is (infra teams, ML teams, data platform teams)
Where economic value is unlocked (compression, compute savings, model accuracy, governance)
How value is quantified (cost curves, workload modeling, infra substitution)
How to convert research capability into revenue and durable platform advantage
This role requires strong intuition around enterprise infra economics.
3️⃣ Research → Durable System
You will:
Identify which modeling advances are worth productionizing
Kill research directions that lack economic or system viability
Define integration paths into enterprise workloads
Work directly with the Chief Research Scientist on research agenda prioritization
Required Background
You must have experience in at least one of:
A) Production AI Systems
Implementing or PM’ing deployment of large models in production
Training infra / inference infra / model maintenance
Operating over structured datasets (Parquet, columnar storage, data lakes)
B) Economic Platform Thinking
Defining buyer, pricing, ROI, and cost structure of AI infrastructure
Converting modeling advantage into business value
Ideally both.
This Role Is NOT
A coordination-heavy research program manager
A consumer AI personalization PM
A pure academic researcher
Core Qualifications
Background in computer science, AI, mathematics, physics, engineering, or a closely related field.
Comfort engaging deeply with researchers and engineers on complex technical topics.
Strong Signals
Experience working with or within a research lab (academic or industrial).
Familiarity with modern AI research workflows, including experimentation, evaluation, and large-scale training.
Ability to abstract at a high level while also diving into details when needed.
Strong written and verbal communication, especially around technical progress and trade-offs.
Bonus Experience
Master’s or PhD in a relevant technical field.
Publications or direct contributions to AI research (e.g., modeling, data, evals, systems, or related areas).
Experience supporting research in structured data, tabular models, or system-aware ML.
Demonstrated ability to learn new technical domains quickly.
Why This Role Matters
Granica is building foundational technology with a long horizon. The research happening here—particularly in structured and tabular AI—is aimed at reshaping how intelligence is built and applied across the global economy.
As a Research Product Manager, you will:
Enable breakthrough research to happen faster and land harder.
Help define how frontier ideas become real systems.
Play a central role in shaping the execution engine behind a generational research agenda.
This role has real ownership, real influence, and a deep connection to the core of the company.
Location & Work Model
This role is office-based in Downtown Mountain View, five days a week. We believe close, in-person collaboration is essential for the kind of deep, cross-disciplinary research and execution this role requires.
Why Granica
Fundamental Research Meets Enterprise Impact. Work at the intersection of science and engineering, turning foundational research into deployed systems serving enterprise workloads at exabyte scale.
AI by Design. Build the infrastructure that defines how efficiently the world can create and apply intelligence.
Real Ownership. Design primitives that will underpin the next decade of AI infrastructure.
High-Trust Environment. Deep technical work, minimal bureaucracy, shared mission.
Enduring Horizon. Backed by NEA, Bain Capital, and various luminaries from tech and business. We are building a generational company for decades, not quarters or a product cycle.
Compensation & Benefits
Competitive salary, meaningful equity, and substantial bonus for top performers
Flexible time off plus comprehensive health coverage for you and your family
Support for research, publication, and deep technical exploration
At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!
