Founded: September 2020
Focus: Machine learning model serving & monitoring
Funding: Series Seed (Redpoint Ventures)
Team: 12 Eng: 10
As enterprises adopt machine learning, the pain of putting models into production has become acute. Data scientists are comfortable working with data locally, but deploying ML models in the cloud is harder, requiring scalable services built with Docker, Kubernetes, and AWS -- well outside their expertise. Aqueduct automates ops for data scientists, enabling them to move faster, build better models, and deliver more value. Aqueduct automatically deploys models, helps monitor them in production, and generates feedback for data scientists to improve over time. Our solution increases efficacy and reduces tiresome ops work.
Aqueduct builds on a years of research from the UC Berkeley RISE Lab. Our team built a best-in-class serverless platform, supporting low-latency function invocation, efficient caching, and smart scheduling. We leverage that serverless technology to simplify operations and improve efficiency for production ML.
As Head of Community at Aqueduct, you will be integral in building a community around our open-source project and our product. The core of our mission is to simplify the lives of data scientists by automating away engineering and ops concerns, and doing that effectively will require careful thought and strong customer empathy. Your goal will be to build and engage with a community of data scientists interested in our technology and to help those data scientists be successful with our product.
Your responsibilities will include: creating and engaging an open-source project community, writing and refining documentation & examples, helping generate technical content for a data science audience, enabling users to succeed with our product, collaborating with engineering and product to scope requirements, and engaging with the broader community (e.g, conferences, meetups).
You are someone who:
- has hands-on experience working as a data scientist or with data scientists
- is excited about improving the productivity of data science teams
- is a great communicator, both in written and spoken forms
- is excited about engaging with data scientists, both on an individual basis and in larger settings like meetups and conferences