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
Own a major technical area of Ray Core end to end, defining the roadmap, identifying the most important technical problems, and driving execution through production. Lead large, technically complex projects spanning multiple engineers, teams, and/or organizations.
What they're looking for
- 6+ years of software engineering experience, with a track record of increasing technical ownership
- Experience leading substantial projects end to end, including defining the problem, creating a roadmap, making architectural decisions, driving implementation, and owning the outcome in production
- Experience leading projects that are larger than a single-engineer effort, typically spanning multiple engineers and lasting multiple quarters
- Deep experience with distributed systems and computer systems
- Strong systems programming experience in languages such as C++, Rust, Java, or similar lower-level languages
- Strong understanding of systems concepts such as multithreading/concurrency, distributed coordination, resource management, fault tolerance, performance, or networking
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.
Own a major technical area of Ray Core end to end, defining the roadmap, identifying the most important technical problems, and driving execution through production.
Lead large, technically complex projects spanning multiple engineers, teams, and/or organizations.
Set technical direction and make architectural decisions for distributed computing infrastructure used by demanding production workloads.
Design, build, and evolve core...
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