Granica

You'll invent algorithms that advance **machine learning for structured and tabular data**, developing **new representation learning techniques** for large enterprise datasets. Core impact: building foundational tabular models that power enterprise AI.

You'll build **self-optimizing data infrastructure** for AI, partnering with a research group to bring advances in information theory to production. Your work will directly reduce cost, latency, and energy waste at scale, making AI more efficient.

You'll lead **strategic finance**, **capital markets**, and **company-wide performance architecture** as Granica's founding finance leader. Your core impact will design the financial engine that scales the company from Series B toward IPO. This role directly shapes **enterprise AI infrastructure economics**.

You'll architect self-optimizing data infrastructure that continuously improves how information is represented and used by AI. Partnering with the Granica Research group, you'll bridge advances in information theory with large-scale distributed systems, driving the next leap in efficient AI infrastructure. This role combines **research breakthroughs** with **production-grade systems** to define the future of AI data.

You'll lead a globally distributed team of senior engineers owning the core data infrastructure for Granica's AI and analytics platforms. You'll drive **table optimization** and **metadata management** at petabyte scale, translating research into production-grade distributed systems. This role combines hands-on technical leadership with team building in a high-bar engineering culture.

You'll define and build core systems for AI model evaluation, post-training feedback loops, and efficient learning over structured data. You'll partner with researchers and engineers to move experiments into production systems used at scale. This role defines **how constraints in evaluation, learning loops, and structured data are solved** to deliver measurable business impact.

You'll join **Granica's core engineering team** to build and scale infrastructure powering **exabyte-scale data systems** and **reliable enterprise AI workloads**. This is a deep engineering role with high technical impact.