Teams at Anyscale

Own the roadmap and technical direction for Ray Core, leading complex distributed-systems projects across multiple teams. Design and implement primitives involving scheduling, resource management, fault tolerance, concurrency, networking, storage, and performance. Remain hands-on in systems-oriented development and debugging while mentoring engineers, raising technical standards, and guiding Ray Core’s long-term architecture and production evolution.

Design, build, optimize, and scale Ray Data’s distributed data processing infrastructure for large-scale AI training and inference. Responsibilities include distributed execution, scheduling, resource management, data partitioning, fault tolerance, performance optimization, and system architecture. The role also involves collaborating with customers and AI-native companies to solve complex workload-scaling challenges.

Develop and maintain Ray’s C++ backend for scalable, reliable distributed computing. Responsibilities include optimizing large-scale workloads, improving fault tolerance, developing open-source software, implementing architectural improvements, enhancing testing infrastructure, leading cross-team projects, mentoring engineers, and communicating technical work through talks, tutorials, and blog posts.