We help ML teams improve their models by improving their datasets
As the first Infrastructure Software Engineer on the Aquarium team, you will drive development of our core product’s underlying technical infrastructure and systems. These services include data streaming pipelines to ingest customer datasets, search indexes for live queries of unstructured data, and user-facing web applications / APIs. Our current tech stack is primarily python based on GCP, with Apache Beam for most batch and streaming data processing jobs.
You will also contribute to the internal infrastructure that all of engineering uses to develop and operate their services. As an expert on reliable, maintainable systems, you will set the direction for our development processes, including building the initial versions of core internal infrastructure and systems.
What you will do
What you should have
Machine learning is eating the world. However, though it’s easier than ever to build a prototype of an ML system, it’s still extremely difficult to build, maintain, and improve ML systems in production to solve real world problems. Aquarium helps teams ship better ML models faster to enable the next generation of revolutionary AI applications.
Aquarium is backed by top investors including Y Combinator and Sequoia Capital. Our customers span many industries, from robotics to agriculture to construction. We’re looking to grow our team with awesome people who’ll shape the future of Aquarium -- both as a product and as a company.
Aquarium helps deep learning teams improve their model performance by improving their datasets.
A model is only as good as the dataset it’s trained on. We help teams find problems with their datasets + models and fix them by editing / adding data to their datasets.