Software Engineer, Supercomputing

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. They are seeking an engineer to design, build, and operate the GPU supercomputing environment that powers large-scale training and inference.

Responsibilities:

• Operate and automate large GPU clusters including provisioning, imaging, and capacity planning
• Write software that abstracts cluster management and presents a unified interface for training and inference
• Extend scheduling/orchestration (Kubernetes, Slurm, or similar) for topology‑aware placement, preemption, quotas, and fair‑share multi‑tenancy
• Monitor and improve operational metrics of speed, reliability, and error recovery
• Build reliable storage and artifact paths for datasets, checkpoints, and logs with clear retention and lineage
• Partner with researchers to unblock scale runs and advise on parallelism and performance trade‑offs