Systems Research Engineer (PhD)

Granica is an AI research and systems company building the infrastructure for a new kind of intelligence: one that is structured, efficient, and deeply integrated with data.

Our systems operate at exabyte scale, processing petabytes of data each day for some of the world’s most prominent enterprises in finance, technology, and industry. These systems are already making a measurable difference in how global organizations use data to deploy AI safely and efficiently.

We believe that the next generation of enterprise AI will not come from larger models but from more efficient data systems. By advancing the frontier of how data is represented, stored, and transformed, we aim to make large-scale intelligence creation sustainable and adaptive.

Our long-term vision is Efficient Intelligence: AI that learns using fewer resources, generalizes from less data, and reasons through structure rather than scale. To reach that, we are first building the Foundational Data Systems that make structured AI possible.

A Deep Tech Approach to AI

We’re unlocking the layers beneath platforms like Snowflake and Databricks, making them faster, cheaper, and more AI-native. We combine advanced research with practical productization, powered by a dual-track strategy:

• Research: Led by Chief Scientist Andrea Montanari (Stanford Professor), we publish 1–2 top-tier papers per quarter.

• Product: Actively processing 100+ PBs today and targeting Exabyte scale by Q4 2025.

WHAT YOU’LL DO

• Build intelligent, autonomous data infrastructure that makes storage feel free and analytics feel instant

• Design and implement adaptive layouts, zone maps, and columnar encodings that slash I/O and unlock true vectorized execution

• Invent and optimize exabyte-scale engines with self-tuning, zero-human-intervention workflows

• Apply deep research (PhD or equivalent) to real-world systems—drive adoption in production

• Evolve resource schedulers, query planners, and shuffle paths for high-throughput, multi-tenant environments

• Build self-healing reliability: chaos-resilient systems with fault injection, retries, and observability by default

• Code across the stack with whatever tool gets the job done: Rust, Go, Spark, CUDA, Java, Scala

WHAT WE’RE LOOKING FOR

• 4+ years engineering in distributed systems, databases, or low-latency infrastructure at companies like MongoDB, Snowflake, Databricks, or similar

• PhD in systems, distributed computing, storage, or adjacent field—or equivalent experience with published research or patents

• Deep fluency in query execution, compilers, compression, indexing, or vectorized computation

• Experience with data systems like Parquet, Delta Lake, Iceberg, Spark, Trino, or Flink

• Proven track record building production-grade infrastructure and making measurable performance gains

• Excellent communicator with a builder-first mindset and systems-level thinking

• 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.

• 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

Join us to build the foundational data systems that power the future of enterprise AI.
At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring.