Spiral builds a fast analytical database for multimodal, multi-rate data streams, on top of the open source Vortex file format. Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such as weather & climate, financial, time-series, genomics, point-clouds, videos, and images. They spend their days waiting on data loaders, writing video or sensor data pipelines, and watching expensive GPUs sit idle on I/O. We make that pain go away.
We’re looking for exceptional engineers with deep experience in low-level, high-performance software and cloud-scale storage systems.
5+ years of experience writing high-quality production code
Strong foundation in operating systems and systems programming
Proven track record in performance engineering
Familiarity with tools like Apache Arrow, Parquet, DataFusion, Clickhouse, or DuckDB is a plus
Understanding of cutting-edge ML infrastructure stack (e.g. PyTorch, CUDA) is also a plus
Experience with Rust is a bonus
Willingness to work in-person at our NYC, SF, or London office
Skills Required
- 5+ years writing high-quality production code
- Deep experience in low-level, high-performance software
- Experience with cloud-scale storage systems
- Strong foundation in operating systems and systems programming
- Proven track record in performance engineering
- Willingness to work in-person at NYC, SF, or London office
- Familiarity with Apache Arrow, Parquet, DataFusion, ClickHouse, or DuckDB
- Understanding of ML infrastructure stack (e.g., PyTorch, CUDA)
- Experience with Rust
What We Do
Spiral is building the data infrastructure that AI needs, enabling teams developing models in complex domains such as weather, climate, financial, time-series, genomics, point-clouds, videos, and images. The company is reinventing storage through innovative data layouts, compression strategies, and orchestration layers, blending open-source building blocks like Vortex with proprietary cloud data warehouse architecture.
