ML Systems Integration Engineer
Cerebras · Sunnyvale, CA · Toronto, CAN
CHECKED 7H AGO
Infrastructureremote
At a glance
Highlights
- Work on the world's largest AI chip, delivering 10x faster inference speeds.
- Bring up next-gen AI hardware systems and supporting software infrastructure.
- Support validation of new hardware generations toward production readiness.
Ideal candidate
A methodical problem-solver who thrives at the hardware-software boundary and enjoys untangling ambiguous system failures alongside hardware engineers.
Requirements
- BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
- Strong programming skills in Python and/or C++
- Excellent debugging and problem-solving skills
- Solid understanding of operating systems fundamentals
- Experience working in Linux development environments
- Understanding of computer architecture and hardware-software interactions
- Strong analytical thinking to break down complex system failures
- Ability to work effectively across multiple engineering teams
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