About the role:Anyscale is looking for a Senior Site Reliability Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision.
Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads.
We are seeking a talented engineers with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale's cloud platform.
You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers.
A snapshot of projects you may work on- 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 to push the boundaries of AI infrastructure
We'd love to hear from you if have- 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 system
- Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments
- Deep understanding of networking, security, and authentication mechanisms in cloud environment
- Familiarity with observability stacks (Prometheus, Grafana etc)
- Proficiency in Go and Python
- Knowledge of low-level operating system foundations (Linux kernel, file systems, containers)
