At Pachyderm, we're building an open-source enterprise-grade data science platform that lets you deploy and manage multi-stage, language-agnostic data pipelines while maintaining complete reproducibility and provenance. If you want to learn more about our grand vision, read what has become our "manifesto."
Our system, developed with open source roots, shifts the paradigm of data science workflows by providing reproducibility, data provenance, and opportunity for true collaboration. Pachyderm utilizes modern technologies like Docker and Kubernetes to build an entirely new method of analyzing data. Offered both as an in-house solution as well as hosted-service, Pachyderm brings together version-control for data with the tools to build scalable end-to-end ML/AI pipelines while empowering users to use any language, framework, or tool they want.
As a open-source product with a vibrant community (2000+ members in our slack channel, 100+ contributors on GitHub), our product documentation, user resources, and product training platform are all fundamental pieces of our success.
We're looking for a Documentation Engineer to lead the implementation of a comprehensive docs strategy; creating content such as new tutorials, architectural diagrams, API docs, and training courses. This is a highly technical role that will require you use and teach our product, understand infrastructure tools such as Kubernetes and Docker and leverage all the various cloud platforms.
The ideal candidate is ex-engineer who loves teaching, creative problem solving, interacting with the community, and is an expert collaborator. While extensive programming experience is not a requirement, you will have the opportunity to do some development work with our docs infrastructure (mkdocs), training tutorial platform (katacoda), and building examples for webinars, conferences, and training videos.