Startups · AI

Software Engineer, ML Developer Experience

Anyscale · San Francisco · Remote

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About Anyscale

Powered by Ray, Anyscale helps AI builders run data-intensive workloads to build and deploy Foundation Models and AI at scale on any cloud. Backed by NEA, a16z and Amplify.

About the role

Design and operate the highly available backend services and platform architecture that power these capabilities across serverless and bring-your-own-cloud environments.

What they're looking for

  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
  • 5+ years of experience writing high-quality production code
  • A solid background in algorithms, data structures, and system design
  • Experience working with modern machine learning tooling — PyTorch, MLflow, data catalogs, and similar
  • Hands-on experience building and operating highly available services in production
  • Strong product instincts and a track record of shipping developer-facing tools that people choose to use
More about this 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.

About the role

Anyscale is looking for a Software Engineer to join the ML Developer Experience (MLDevX) team. MLDevX owns the experience layer of the Anyscale platform: the interfaces through which users and coding agents discover, configure, run, observe, debug, and productionize AI workloads. Every user journey crosses this layer through the CLI, SDKs, APIs, UI, Workspaces, MCP, or the workflows and integrations built on top of them....

Read the full posting on Anyscale's site ↗

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