At Iterative, we believe the future of machine learning depends on treating data with the same care and precision as code. Our team of engineers and data scientists is building a new paradigm for ML infrastructure - one where datasets are versioned, experiments are reproducible, and collaboration is seamless. We're remote-first by design, with team members spanning continents and time zones, united by a shared conviction that open-source tools can democratize AI development.
We shipped DVC (Data Version Control) to give ML teams Git-like capabilities for their datasets and models, enabling data scientists to track experiments, reproduce results, and collaborate without friction. Today we're expanding that vision with DataChain, a platform for indexing and processing massive multimodal datasets - video, sensors, medical imaging - at scale. Our engineers ship production code daily, engage directly with our open-source community on GitHub and Discord, and work hand-in-hand with enterprise customers to solve real ML infrastructure challenges. We optimize for focus, not facetime, and believe the best work happens when talented people have the autonomy to own problems end-to-end.