Member of Technical Staff — Compute Cluster
Causal Labs· Infrastructure
San FranciscoFull-timePosted 2mo ago
About the role
Build and operate the supercomputing environment for large distributed GPU clusters to enable rapid research iteration in AI for physics, including training, evaluation, and serving on a GPU fleet.
Responsibilities
- 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
Qualifications
- Experience operating large-scale GPU clusters and container orchestration frameworks (e.g. Kubernetes, Slurm, Docker)
- Strong systems background: Linux, networking, storage, 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
- Familiarity with CUDA/NCCL and performance profiling for distributed workloads
- Owns deliverables end-to-end, from requirements through autonomous execution
Skills
Required:GPU cluster operationContainer orchestrationLinux systemsObservability and version control
Nice to have:Cloud platforms and ML servicesCUDA/NCCL
Last updated Aug 7, 2026. Interested? Apply on the company site.
About Causal Labs
Towards general causal intelligence
Causal Labs is building a Large Physics foundation Model (LPM) to learn causality through physics and weather
causalityphysicsweatherAIfoundation model
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