About Anyscale:
At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.
With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.
About The Role
We’re looking for passionate, motivated engineers excited to build infrastructure and tools for the next generation of machine learning applications. We’re hiring exceptional Software Engineers for our distributed training team, which develops and maintains widely adopted open-source machine learning libraries.
We’re particularly interested in engineers who can help shape and execute a vision for the future of ML training infrastructure. We welcome both Individual Contributors and technically inclined individuals with experience managing small teams.
About The Distributed Training Team
The Distributed Training team drives the development and optimization of Ray’s distributed training libraries, focusing on features and performance enhancements for large-scale machine learning workloads. They are responsible for building and maintaining core libraries like Ray Train (for distributed model training) and Ray Tune (for distributed hyperparameter tuning). You’ll collaborate closely with the Ray Core and Ray Data teams to create impactful, end-to-end solutions, and have the exciting opportunity to work directly with Machine Learning teams around the globe, shaping products that are transforming the AI landscape.
About The Role
We’re looking for passionate, motivated engineers excited to build infrastructure and tools for the next generation of machine learning applications. We’re hiring exceptional Software Engineers for our distributed training team, which develops and maintains widely adopted open-source machine learning libraries.
We’re particularly interested in engineers who can help shape and execute a vision for the future of ML training infrastructure. We welcome both Individual Contributors and technically inclined individuals with experience managing small teams.
About The Distributed Training Team
The Distributed Training team drives the development and optimization of Ray’s distributed training libraries, focusing on features and performance enhancements for large-scale machine learning workloads. They are responsible for building and maintaining core libraries like Ray Train (for distributed model training) and Ray Tune (for distributed hyperparameter tuning). You’ll collaborate closely with the Ray Core and Ray Data teams to create impactful, end-to-end solutions, and have the exciting opportunity to work directly with Machine Learning teams around the globe, shaping products that are transforming the AI landscape.
As part of this role, you will:
We'd love to hear from you if have:
Bonus points if:
Compensation:
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish
About Anyscale:
At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.
With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.