Cluster Operations Software Engineer

Cerebras Systems•Sunnyvale, CA

2d•Hybrid

About The Position

We are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power. You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.

Requirements

6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments.
Experience and Expertise in distributed systems is a must.
Deep understanding of Linux-based compute systems and command-line tools.
Extensive knowledge of Docker containers and container orchestration platforms like k8s.
Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
Experience with monitoring and alerting systems.
Should have a proven track record to own and drive challenges to completion.
Excellent communication and collaboration skills.
Ability to work effectively in a fast-paced environment.
Willingness to participate in a 24/7 on-call rotation.

Nice To Haves

Operating and Managing large scale AI clusters.
Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).

Responsibilities

Deploy, configure, and debug container-based services using Docker.
Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling.
Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities.
Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure.
Manage and operate multiple advanced AI compute infrastructure clusters.
Monitor and oversee cluster health, proactively identifying and resolving potential issues.
Maximize compute capacity through optimization and efficient resource allocation.
Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.
Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.
Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.