Software Engineer (Machine Learning)

San Francisco, CA /
Engineering /
Full-time
About the role:
One of the things that makes Python great is the fact that it has great libraries. Developers can import numpy and pandas and start building powerful applications. But in the distributed setting today, we don’t have libraries. Instead, we have distributed systems like Spark, Horovod, and TensorFlow Serving. These systems cannot easily be composed together and used as elements of a larger application. For example, an online learning system that ingests streaming data, incrementally trains new recommendation models, and then serves recommendations to users will have to stitch together three different distributed systems (one for streaming, one for training, and one for serving) just to build a single application. In the future, people will build these kinds of applications by importing powerful distributed libraries from a rich ecosystem and by composing them together to build new applications. Help us build that ecosystem. This will include libraries for reinforcement learning, hyperparameter tuning, experiment management, model serving, distributed training, and more. Part of this work will be open source as part of Ray.

We are looking for senior hires as well as less experienced but motivated individuals.

About Anyscale:
Anyscale provides an application development platform for developers to build distributed applications. 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. Our goal is to build a standardized platform for distributed computing. Ray was developed at UC Berkeley by Robert Nishihara and Philipp Moritz, under the guidance of Ion Stoica and Michael Jordan, and the four of them have co-founded Anyscale. The company raised a $20.6M Series A funding led by Andreessen Horowitz (a16z) with participation from NEA, Intel Capital, Ant Financial, Amplify Partners, 11.2 Capital, and The House Fund.

With Ray, we're making it easy to program at any scale (from your laptop to the datacenter) by providing easy-to-use, general-purpose, and high-performance tools. In addition, we are building a rich ecosystem of libraries (for reinforcement learning, hyperparameter search, experiment management, machine learning training, prediction serving, and more) on top of the core distributed system so that users can rapidly build sophisticated applications. Help us build the future of software development.

We are looking for passionate, motivated people who are excited to build tools to power the next generation of cloud applications.

We are hiring strong software engineers for a variety of roles. Examples include:

As part of your role you will

    • Develop high quality software to empower software developers and simplify programming
    • Work with a team of leading distributed systems and machine learning experts
    • Communicate your work to a broader audience through talks, tutorials, and blog posts
    • Help us to build and shape a world class company

Requirements:

    • At least 2 years of relevant work experience
Must be willing to work onsite in our office.

We are excited to build a diverse team and encourage all to apply!