AI Datacenter Infra engineer
Cerebras · Toronto, CAN · Remote (US) · Sunnyvale, CA
CHECKED 8H AGO
Infrastructureremote
At a glance
Highlights
- Turn cluster architectures into precise, deployment-ready data center designs.
- Own rack layouts, power allocations, and port and cable mappings.
- Support deployment teams resolving physical integration issues at scale.
Ideal candidate
Detail-oriented systems thinker with data center design experience who enjoys practical problem-solving and cross-functional collaboration to deliver reliable, scalable AI infrastructure.
Requirements
- Bachelor's or master's in computer engineering, electrical engineering, computer science or related field or equivalent experience
- 1+ years in infrastructure engineering, data center design, systems integration, hardware deployment or related field
- Experience creating or working with rack elevations, equipment layouts, BOMs, port maps, or cable maps
- Practical understanding of server, storage, and networking hardware and physical integration
- Familiarity with data center power, cooling, space, cabling, and serviceability constraints
- Experience using Python, Bash, PowerShell, or another language to automate technical workflows
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