About the Role
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. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. The ML Developer Experience team is responsible for creating the suite of tools and services that enable users to create production quality applications using Ray. The product is the user’s primary interface into the world of Anyscale and by building a polished, stable, and well-designed product, we are able to enable a magical developer experience for our users. This team provides the interface for administering Anyscale components including Anyscale workspaces, production and development tools, ML Ops tools and integrations, and more. Beyond the user-facing features, engineers help build out critical pieces of infrastructure and architecture needed to power our platform at scale. With a taste for good products, a willingness to work with and understand the user base, and technical talent to build high quality software, the engineers can help build a delightful experience for our users from new developers learning to use Ray to businesses powering their products on Anyscale.
Responsibilities
- Develop a next-gen ML Ops platform and development tooling centered around Ray
- Build tools and frameworks for managing the AI development lifecycle from data preparation to training to production serving
Requirements
- A solid background in algorithms, data structures, and system design.
- Experience working with modern machine learning tooling, including PyTorch, MLFlow, data catalogs, etc.
- At least 5+ year of relevant work experience
Qualifications
- Experience in building and maintaining open-source projects.
- Experience in building and operating machine learning infrastructure in production.
- Experience in building highly available serving systems.