Research Product Manager — AI Systems (Structured Data, Evaluation & Learning Efficiency)

Location: Mountain View, CA
Work Model: On-site (5 days/week)
Employment Type: Full-time
Team: Research

The Mission

AI progress is no longer limited by model architecture.

The bottleneck is:

• how models are evaluated

• how they improve after training

• how they behave in real-world systems

Granica is building the systems that solve this.

We are a systems and research company led by Stanford Professor Andrea Montanari, focused on:

• evaluation as a first-class system

• post-training as a continuous learning loop

• efficient learning over real-world data

Most real-world data is structured and relational, yet modern AI systems remain poorly optimized to learn from it.

Our thesis:

AI advantage will come from how efficiently models learn from structured data and translate that into economic value.

The Role

This is a Research Product Manager role focused on AI systems and structured data learning.

You will define systems that determine:

• how models are evaluated

• how models learn from structured and relational data

• how improvements propagate through training and inference

• how performance translates into economic outcomes

You will operate at the boundary of:

research × systems × product

This role focuses on defining new system primitives, not executing predefined roadmaps.

What You’ll Drive

Evaluation & model behavior

• Define evaluation frameworks for correctness, reliability, and real-world performance

• Build systems to measure and improve model behavior in production

Learning loops & lifecycle

• Design feedback and post-training systems that continuously improve models

• Define workflows across training, inference, and iteration

Structured data systems

• Define how models learn from large-scale tabular and relational data

• Bridge data systems (warehouses, lakehouses) with ML systems

Efficiency & economic impact

• Model trade-offs across compute, data efficiency, and performance

• Identify where system improvements drive cost or revenue impact

Research → production

• Translate research into scalable systems and platform capabilities

• Drive the path from prototype to production infrastructure

What We’re Looking For

We’re looking for candidates who think in terms of:

• model evaluation and behavior

• learning systems and feedback loops

• structured / relational data systems

• efficiency and economic impact

Technical depth

• Experience in ML systems, AI infrastructure, or data platforms

• Strong understanding of training, evaluation, and deployment

Systems thinking

• Ability to reason about trade-offs across data, compute, and performance

• Experience working with large-scale or distributed systems

Structured data experience

• Experience with relational or tabular data systems

• Familiarity with modern data platforms (e.g., warehouses, lakehouses)

Product judgment

• Ability to translate technical systems into platform capabilities

• Experience connecting system improvements to real-world outcomes

• Comfort operating in ambiguous, research-driven environments

Ideal Backgrounds

• AI/ML infrastructure PMs (Meta, OpenAI, Google, Snowflake, Databricks, AWS, AI start ups or similar)

• ML platform or LLM systems product leaders

• Product leaders in evaluation, observability, or model systems

• Research engineers or applied scientists moving into product

• Engineers who have built ML/data systems and taken product ownership

Seniority

• Senior / Staff Product Manager

• Principal / Head of Research Product (for exceptional candidates)

Why This Role Matters

Most AI systems are limited not by model capability, but by:

• weak evaluation systems

• inefficient learning loops

• poor utilization of structured data

• lack of connection between model performance and economic value

This role defines how those constraints are solved in production systems.

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!