Senior Site Reliability Engineer, Platform Infrastructure (Foundations)
데브옵스 엔지니어정규직시니어 · 3년 이상
Anyscale에서 분산 AI 인프라를 구축할 시니어 SRE를 채용합니다. Kubernetes 및 클라우드 네이티브 환경에서의 대규모 시스템 운영 경험이 필수입니다. Go와 Python을 활용해 Ray 클러스터의 제어 및 데이터 평면을 최적화하고, 고성능 분산 컴퓨팅 환경을 설계하는 핵심 역할을 수행하게 됩니다.
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.
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.
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
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)
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish