Member of Technical Staff — Cluster/Platform

Responsibilities

• Architect and scale large AI compute clusters for training and inference
• Design cluster management, scheduling, and resource allocation systems
• Optimize performance, utilization, and reliability of GPU/TPU clusters
• Improve fault tolerance and system resilience at scale
• Drive observability, monitoring, and performance profiling for cluster infrastructure
• Collaborate with ML and systems engineers to support frontier AI workloads
• Lead capacity planning and infrastructure scaling strategies
• Build internal platforms and tooling to improve developer productivity
• Document architecture, operational practices, and reliability strategies
• Contribute to long-term platform vision and technical direction

Requirements

• 5+ years of experience in distributed systems, infrastructure, or large-scale compute platforms
• Strong background in distributed systems design and systems architecture
• Deep experience with cluster management systems (Kubernetes, Slurm, Ray, or custom schedulers)
• Hands-on experience with GPU/TPU infrastructure in production environments
• Strong Linux systems and networking fundamentals
• Proficiency in Go, Rust, C++, or Python for production systems
• Experience debugging complex multi-layer issues across hardware, OS, networking, and distributed services
• Proven ability to design reliable, scalable systems in production

Preferred Qualifications

• Experience with large-scale ML/AI workloads
• Familiarity with RDMA, InfiniBand, or high-performance networking
• Experience operating clusters at 1000+ GPU scale
• Background in HPC or performance-critical systems
• Open-source contributions in systems or infrastructure

About the Company

RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems, created SGLang, and developed Miles. We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training.