Causal
Member of Technical Staff — Compute Cluster
San Francisco. Posted 3 months ago
The role
You will design, build, and operate a supercomputing environment. This involves managing a GPU fleet to deliver performant, reliable, and cost-efficient compute for research.
What you will do
- Design, deploy, and operate large distributed GPU clusters end to end
- Extend scheduling and orchestration systems like Kubernetes and Slurm
- Build software that abstracts cluster management for researchers and engineers
- Own cluster storage and artifact paths for checkpoints and logs
- Monitor and continuously improve reliability and error recovery
- Partner with researchers to unblock large-scale runs and advise on performance
Required qualifications
- Experience operating large-scale GPU clusters and container orchestration frameworks
- Strong systems background in Linux, networking, storage, and infrastructure-as-code
- Knowledge of cloud platforms and their ML/AI service offerings
- Understanding of monitoring, logging, observability, and version control best practices for ML systems
- Familiarity with CUDA/NCCL and performance profiling for distributed workloads
- Owns deliverables end-to-end, from requirements through autonomous execution
About the company
Causal is building a Large Physics foundation Model to achieve general causal intelligence. The founding team has built and deployed AI at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.