Cluster Operations Software Engineer
About The Position
Cerebras Systems builds the world's largest AI chip, the Wafer-Scale Engine (WSE), which is 56 times larger than GPUs. This architecture enables industry-leading training and inference speeds, transforming AI applications and unlocking real-time iteration. Cerebras collaborates with leading AI organizations, including a significant partnership with OpenAI. The company is seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate its advanced machine learning compute clusters. This role offers the opportunity to work with the WSE and its supporting systems, ensuring the health, performance, and availability of the infrastructure, maximizing compute capacity, and supporting AI initiatives. The position requires a strong understanding of Linux-based systems, containerization, and experience with monitoring and troubleshooting distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependability, and a commitment to 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.
Benefits
- Job stability with startup vitality
- Simple, non-corporate work culture that respects individual beliefs
- Continuous learning, growth and support of those around them
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
