Distributed Software Engineer
Cerebras · Toronto, CAN
CHECKED 6H AGO
Infrastructureremotesenior
At a glance
Highlights
- Turn thousands of wafers, servers and switches into a cloud that stays up.
- Build push-button cluster install, upgrades and patching with downtime budgets.
- Help deliver 10x faster inference than GPU clouds for leading AI labs.
What they offer
- Build a breakthrough AI platform beyond the constraints of the GPU
- Publish and open source cutting-edge AI research
- Work on one of the fastest AI supercomputers in the world
- Job stability with startup vitality
- Simple, non-corporate work culture that respects individual beliefs
Ideal candidate
Self-driving infrastructure engineer who thrives in large, fast-moving, undocumented environments and cares about keeping massive fleets healthy, busy and debuggable.
Requirements
- 5+ years building and operating production distributed systems or infrastructure software
- Production-quality Go and Python
- Real Kubernetes depth including controllers, operators, CRDs, reconciliation, informers, admission webhooks and RBAC
- Strong debugging across distributed systems, Linux and networking
- Practitioner-level Prometheus and Grafana including PromQL, exporter design and alerting
- Strong self-driving capability with fast learning speed in large, undocumented environments
- Demonstrated adoption of AI in engineering workflow with rigorous verification
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