Staff AI Scheduling Engineer

To lead the workload placement logic for the AI-native NeoCloud platform, the full-time Staff AI Scheduling & Orchestration Engineer will design advanced scheduling architectures and optimize resource utilization in a remote role based in San Jose, CA or Austin, TX. Key Responsibilities Design and implement advanced batch scheduling architectures using frameworks like Volcano or YuniKorn for multi-node gang scheduling Develop cluster-wide admission control and job queueing mechanisms to manage high-volume AI workload traffic Architect topology-aware pod placement strategies to optimize low-latency communication via NVLink and InfiniBand fabrics Required Qualifications Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field 6+ years of distributed systems engineering with expertise in Kubernetes scheduling frameworks Extensive experience with AI workload execution patterns and distributed training frameworks Proven track record in operating and scaling scheduling stacks in high-performance computing environments Strong knowledge of GPU hardware architectures and associated scheduling challenges