Cerebras Systems
AI Infrastructure Operations Engineer
Sunnyvale CA or Toronto Canada
Sponsorship not specifiedDetected 97 days ago
PythonAWSGCPAzureDockerKubernetesLinuxMachine LearningLLMsComplianceTCP/IPCommunicationCollaboration
About the role
- These clusters would provide the candidate 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.
- The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.
Responsibilities
- Manage and operate multiple advanced AI compute infrastructure clusters.
- 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.
- Contribute to the development and improvement of our monitoring and support processes.
Requirements
- Experience with cross-functional team projects.
- This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems.
Skills
- Strong proficiency in Python scripting for automation and system administration.
- Deep understanding of Linux-based compute systems and command-line tools.
- Extensive knowledge of Docker containers and container orchestration platforms like k8s and SLURM.
- Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
- Experience with monitoring and alerting systems.
- Excellent communication and collaboration skills.
- Ability to work effectively in a fast-paced environment.
- Willingness to participate in a 24/7 on-call rotation.
- Operating large scale GPU clusters.
- Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
- Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).
- Familiarity with machine learning frameworks and tools.
Benefits
- Monitor and oversee cluster health, proactively identifying and resolving potential issues.
- 6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
Company info
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
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This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.