About Anyscale:
Anyscale provides a development platform intended to simplify distributed computing. This enables software developers of all skill levels to build applications that run at any scale from a laptop to the data center.
We're commercializing a popular open source project called
Ray - which is a framework for distributed computing as well as an ecosystem of libraries for scalable machine learning.
Anyscale is based in San Francisco, CA.
About the role:
Anyscale is looking to hire strong individuals to develop open source machine learning libraries.
The software industry largely operates on a messy zoo of specialized distributed systems such as Spark, Horovod, and TensorFlow Serving. These systems cannot easily be composed together and used as elements of a larger application. On the Machine Learning Ecosystem team at Anyscale, we are developing a rich ecosystem that will allow developers to import powerful distributed libraries and compose them together to build new applications.
Part of this work will be open source as part of Ray, which is a distributed Python execution engine as well as an ecosystem of libraries for scalable machine learning.
About the Libraries team :
The Libraries team’s mission is to make it really easy to do distributed machine learning on Ray and Anyscale. Specifically, our team maintains and develops features for a broad number of libraries — including RaySGD (distributed deep learning), Ray Tune (distributed hyperparameter tuning), RLlib (reinforcement learning), and XGBoost-on-Ray.
Our team is the most user-facing engineering team on the open source side, collaborating with ML engineering teams at organizations like Shopify, Uber, and Bytedance.