Causal Labs
Member of Technical Staff — Compute Cluster
San Francisco · On-site · Staff · Full-time · Posted Jul 19, 2026
About the job
Designs, builds, and operates the GPU supercomputing environment that supports the company’s AI training, evaluation, and serving workloads.
What you'll do
- Deploy and operate distributed GPU clusters, including provisioning, upgrades, and capacity planning.
- Extend scheduling and orchestration for training and inference workloads, and build self-serve cluster management software.
- Manage cluster storage, reliability, observability, and recovery; partner with researchers on large-scale runs and performance trade-offs.
What they ask for
- 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 (GCP, AWS, or Azure) and their ML/AI service offerings.
- Understanding of monitoring, logging, observability, and version control best practices for ML systems.
Nice to have
- Familiarity with CUDA/NCCL and performance profiling for distributed workloads.
Tools
Kubernetes, Slurm, Docker, Linux, GCP, AWS, Azure, CUDA/NCCL
AI focus
The infrastructure supports development of a Large Physics foundation Model for predicting and controlling physical systems, starting with weather.
Model-written summary · the original posting is authoritative