Applied AI Research Engineer – ML Systems & Structured Data
APPLIED AI RESEARCH ENGINEER – ML SYSTEMS & STRUCTURED DATA
Location: Bay Area (Mountain View)
Employment Type: Full-time
Work Model: On-site
Department: Research
Compensation: $160K – $250K + Equity
OVERVIEW
Granica is building the next generation of efficient AI infrastructure.
Today’s AI systems are limited not only by model design but by the inefficiency of the data that feeds them. At enterprise scale, redundant data, inefficient representations, and poorly optimized learning pipelines create enormous cost and latency.
Granica’s mission is to eliminate that inefficiency.
We combine advances in information theory, machine learning, and distributed systems to design data infrastructure that continuously improves how information is represented and used by AI.
Granica’s research effort is led by Prof. Andrea Montanari (Stanford) and focuses on building learning systems that operate efficiently on large-scale structured and tabular data.
While much of the industry focuses on text or media models, Granica is building the foundations of AI systems that learn directly from structured enterprise data.
This role focuses on building machine learning systems for structured and tabular data rather than general LLM application development.
THE ROLE
The Applied AI Research Team sits at the intersection of theory and production.
Your work will take ideas emerging from fundamental research and turn them into practical algorithms, optimized pipelines, and production-ready ML systems that operate across petabytes of structured enterprise data.
This is a high-ownership role for engineers who can think like researchers and build like systems engineers.
You will translate theory into measurable performance improvements and help define the engineering foundations of structured AI.
WHAT YOU’LL DO
TURN RESEARCH INTO WORKING SYSTEMS
- Transform foundational ideas from Granica Research and Prof. Andrea Montanari’s group into scalable algorithms and prototypes
-...