Software Engineer, Ray Serve

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, 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.

Anyscale is actively seeking talented engineers to join our team and contribute to the development of next-generation, high-performance machine learning serving systems. We value diversity and inclusion, and we encourage individuals from underrepresented groups to apply.

Many existing ML serving tools are inherited from previous infrastructure generations, but emerging ML applications present new requirements, such as high compute demands, specialized hardware needs, and the integration of multiple models and business logic within a single request. At Anyscale, our mission is to provide a powerful yet simple set of tools that enable the seamless deployment of complex ML applications in production.

The Challenge

What if you could build the infrastructure that powers AI applications for millions of users worldwide? Ray Serve is the production-grade serving framework that makes this possible—and we need exceptional engineers to push its boundaries.

You'll be working on problems that sit at the intersection of distributed systems, machine learning, and high-performance computing. This isn't about maintaining CRUD apps or tweaking configurations—this is about solving fundamental computer science problems that directly impact how the world deploys AI.

What You'll Actually Build

Example projects:

• Asynchronous inference: Let the client submit a request and get a request handle that asks for its requests completion while not blocking the client side. Really important for image, video, or audio generation applications.