SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Anyscale is commercializing Ray, an open-source distributed computing framework used by companies like OpenAI, Uber, Spotify, Instacart, and Cruise to power AI and ML workloads at scale. The company has raised $250M+ from top-tier investors including Andreessen Horowitz and NEA.
As a Staff Software Engineer on Ray Core, you will own a major technical area of the Ray Core platform end-to-end. This is a high-impact role where you will define roadmaps, identify critical technical problems, and drive execution through production. You'll lead large, technically complex projects spanning multiple engineers, teams, and organizations, setting technical direction and making architectural decisions for distributed computing infrastructure that powers demanding production workloads.
Your day-to-day work will involve designing and building core distributed-systems primitives—not simply integrating existing platforms. You'll work on problems spanning distributed execution, scheduling, resource management, fault tolerance, concurrency, networking, storage, and system performance. You'll stay hands-on with implementation and debugging in a systems-oriented codebase while mentoring engineers and raising the technical bar across teams. You'll also help shape the longer-term architecture and evolution of Ray Core as workloads and scale continue to grow.
This role is ideal for someone who thrives on deep technical challenges, has a track record of leading large projects to completion, and is passionate about building infrastructure that enables others to scale AI and ML applications effortlessly.
REQUIREMENTS:
- 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 roadmaps, making architectural decisions, driving implementation, and owning production outcomes
- Experience leading projects larger than a single-engineer effort, typically spanning multiple engineers and lasting multiple quarters
- Deep experience with distributed systems and computer systems (not primarily using existing distributed platforms)
- Strong systems programming experience in 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
- Experience working on systems such as databases, streaming systems, distributed runtimes, operating systems, schedulers, storage systems, Spark, Kafka, or similar infrastructure
- Track record of mentoring engineers and raising the technical bar of teams around you
- Nice to have: Contributions to open-source infrastructure projects
About Anyscale
AI / Data / Infrastructure — distributed computing and AI workload platform built around Ray.
