Senior AI Infrastructure Engineer to lead the vision, execution, and long-term stability of how Company trains with GPUs at scale. In this role, you will take absolute ownership of cluster robustness, ensuring our high-performance GPU systems are highly available, fault-tolerant, and resilient for ML platform and research teams company-wide. This is a highly hands-on role where your primary focus is logical stability and automated resilience—building self-healing mechanisms to proactively detect and isolate hardware faults, tuning NCCL and high-speed networking, and optimizing Kubernetes, Run: AI, and Ray scheduling. By replacing manual triage with automated deployment tooling and deep observability, you will ensure our massive-scale training infrastructure runs seamlessly and scales without linear headcount growth.
