Member of Technical Staff — Compute Cluster
Causal Labs, San Francisco
What you will do
- Design, deploy, and operate large distributed GPU clusters end to end: provisioning, imaging, upgrades, and capacity planning
- Extend scheduling and orchestration systems (e.g. Kubernetes, Slurm) for topology-aware placement, preemption, quotas, and multi-tenancy across training and inference workloads
- Build software that abstracts cluster management and presents a unified, self-serve interface to researchers and engineers
- Own cluster storage and artifact paths for checkpoints and logs, with clear retention and lineage
- Monitor and continuously improve reliability and error recovery; build the observability to catch failures before researchers do
- Partner with researchers to unblock large-scale runs and advise on performance and placement trade-offs
What you need
We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.