Staff AI Scheduling Engineer

Job Summary

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