Software Engineer, Infrastructure

Responsibilities

• Design, build, and scale services that orchestrate Ray clusters across cloud and on-prem environments, supporting both VM-based and Kubernetes-based deployments.
• Optimize control plane components for large-scale, distributed AI/ML workloads.
• Build intelligent scheduling and resource management systems for heterogeneous compute clusters.
• Develop features to enhance the reliability, performance, scalability, and observability of Anyscale-managed Ray workloads.
• Support and optimize accelerator integration (e.g., GPUs, TPUs).
• Handle container image management and dependency resolution for distributed workloads.
• Participate in code reviews, design and architecture discussions.
• Provide on-call support, working closely with customer and field teams to troubleshoot infrastructure issues.
• Collaborate with leading distributed systems and machine learning experts.

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years of experience writing high-quality production code.
• Hands-on experience in building and maintaining highly available, scalable, and performant distributed systems.
• Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments.
• Deep understanding of networking, security, and authentication mechanisms in cloud environments.
• Familiarity with observability stacks (Prometheus, Grafana etc).
• Proficiency in Go and Python.
• Knowledge of low-level operating system foundations (Linux kernel, file systems, containers).