Site Reliability Engineer, Platform Infrastructure (Foundations)

Carbon Data Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Anyscale is seeking a Site Reliability Engineer to join the Infra team. You will help build the scalable backbone for distributed AI workloads in the cloud, designing both control and data plane components and optimizing scheduling across cloud and on-prem environments.

You will work on open-source Ray, integrate with our proprietary platform, and collaborate with ML and systems experts to push AI infrastructure forward.

Qualifications

• Bachelor's degree in CS, Eng, or equivalent.
• 3+ years of production code experience.
• Experience building highly available distributed systems.
• Expertise in cloud-native tech and Kubernetes deployments.
• Strong knowledge of networking, security, and authentication in cloud environments.

Responsibilities

• Design, build, and scale services that orchestrate Ray clusters across cloud and on-prem environments.
• 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 reliability, performance, scalability, and observability of 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 and collaborate with customer and field teams to troubleshoot infrastructure issues.
• Collaborate with distributed systems and ML experts to push AI infrastructure boundaries.

Skills

Go

Python

Distributed systems

Networking

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

Kubernetes

Prometheus

Grafana

AWS

Azure

GCP

Job description

About Anyscale:

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.

About the role:

Anyscale is looking for a 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)

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.