Cluster Operations Software Engineer
Cerebras · Sunnyvale, CA · Toronto, CAN · Bengaluru, IND
CHECKED 8H AGO
Infrastructureremotesenior
At a glance
Highlights
- Operate cutting-edge ML clusters powered by the Wafer-Scale Engine.
- Maximize compute capacity for ultra high-speed AI training and inference.
- Support global AI initiatives with industry-leading model labs and startups.
Ideal candidate
Proactive problem-solver with years operating large-scale compute infrastructure who thrives in fast-paced settings. Dependable collaborator passionate about maximizing reliability and customer success for cutting-edge AI.
Requirements
- 6-8 years managing and operating complex compute infrastructure, preferably ML or HPC
- Proficient in Python and Go building operational platforms and reliability tooling
- Expertise in distributed systems
- Deep understanding of Linux-based compute systems and command-line tools
- Extensive knowledge of Docker and container orchestration like Kubernetes
- Experience with monitoring and alerting systems
- Proven ability to troubleshoot complex issues and drive challenges to completion
- Excellent communication and collaboration skills with ability to work in fast-paced environment
- Willingness to participate in 24/7 on-call rotation
- Experience operating large-scale AI clusters
- Knowledge of Ethernet, RoCE, TCP/IP
- Knowledge of cloud platforms like AWS, GCP, Azure
Lab profile
About Cerebras
Builds wafer-scale AI chips and cloud systems for ultra-fast training and inference.
What they build
- Wafer-scale AI chips
- AI training systems
- Cloud inference service
Known for
- 56x larger chips than GPUs
- 10x faster inference than GPU clouds
- Industry-leading training speed