Anyscale

Staff Software Engineer leading the technical vision and architectural evolution of Anyscale’s platform infrastructure for large-scale distributed AI workloads. The role focuses on Kubernetes-based cloud infrastructure, control and data planes, reliability, scalability, and technical leadership across teams.

Lead the evolution of Ray Core as a Staff Software Engineer, owning major technical areas and building foundational distributed-systems primitives for demanding production workloads. You’ll remain hands-on while setting architecture, driving complex projects, and mentoring engineers.

Build and scale Ray Data, a Python-native distributed data processing engine powering large-scale AI training and inference workloads. This staff-level role focuses on distributed systems, performance, fault tolerance, and architectural decisions for multimodal and structured data.

Build and improve Ray’s C++ distributed-systems backend, focusing on performance, reliability, scalability, and fault tolerance. The role combines hands-on systems software development with technical leadership, mentoring, and open-source communication.

Anyscale is hiring a Software Engineer for its ML Developer Experience team to build developer tooling, APIs, platform services, and workflows that make distributed AI workloads easier to develop, operate, and scale on Ray. This high-impact individual-contributor role spans the full machine learning and developer experience lifecycles.

Anyscale is seeking a Senior Product Security Engineer to own its secure software development lifecycle and embed security throughout product engineering. The role combines hands-on security architecture, vulnerability management, secure-development tooling, and cross-functional security leadership.

Own and strengthen Anyscale’s cloud and production infrastructure security across multi-cloud and Kubernetes environments. This hands-on senior role drives hardening, runtime protection, access control, and remediation strategy.

Join Anyscale’s Infrastructure team as a Site Reliability Engineer building the scalable control-plane and data-plane systems that power distributed AI workloads. You’ll work across Kubernetes, cloud infrastructure, Ray, scheduling, observability, and reliability for cloud and on-premise deployments.