Head of Ray Core / Ray Ecosystem ( Director of Engineering)

Anyscale•San Francisco, CA

49d

About The Position

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: Ray Core is the foundational distributed runtime at the heart of Ray. It is responsible for cluster scheduling, distributed execution, fault tolerance, resource management, and the APIs that higher-level Ray libraries and ecosystem projects are built upon. We are looking for a Director of Engineering to lead the Ray Core Engineering organization / Ray OSS Ecosystem. This role owns the technical and organizational direction of one of the most critical components of Ray and plays a central role in shaping Ray as long-term infrastructure used across the ML and data ecosystem. This is a deeply technical leadership role. You will partner closely with senior engineers, researchers, and product leaders, and you will be expected to engage meaningfully in systems design, architectural decisions, and technical tradeoffs.

Requirements

8+ years of software engineering experience, with significant time spent building distributed systems or systems infrastructure
5+ years of experience leading and scaling engineering teams, ideally including managers
Strong background in one or more of: distributed systems and/or databases schedulers, runtimes, or control planes cloud infrastructure or large-scale backend systems
Deep understanding of systems fundamentals such as: concurrency and parallelism fault tolerance and consistency performance and resource isolation
Experience working with or leading open-source software (as a maintainer, contributor, or heavy user)
Ability to operate as a player-coach: comfortable diving into technical details while leading at the organizational level
Strong communication skills and a track record of making sound technical tradeoffs in complex systems

Nice To Haves

Experience with Ray, Spark, Kubernetes, or similar distributed frameworks
Background in ML systems, data systems, or large-scale compute platforms
Experience leading teams responsible for widely used, long-lived APIs

Responsibilities

Lead and grow a team of senior engineers working on Ray Core and adjacent ecosystem components
Act as a technical leader in the open-source Ray community, setting standards for design, quality, and collaboration.
Own the growth and adoption of OSS Ray
Own the technical vision and roadmap for Ray’s distributed runtime, including: cluster scheduling and resource management distributed execution and control-plane architecture fault tolerance, recovery, and correctness performance, scalability, and efficiency
Drive high-quality systems design and architecture, including RFCs, design reviews, and long-term API strategy
Ensure Ray Core continues to scale across: larger clusters and heterogeneous hardware increasingly diverse workloads (ML, data, agents, serving) a growing open-source user and contributor base
Partner cross-functionally with product, research, and go-to-market teams to align technical execution with company strategy
Develop and mentor engineering leaders and senior ICs, fostering a strong culture of technical excellence and ownership