Director of AI Infrastructure

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter. Our base salary range is $176,400 - $264,600, and in addition we have generous bonus plans to provide a competitive compensation package.  Who We Are:  Ai2 is a non-profit research institute at the forefront of open-source AI development. Unlike industry peers, our goal is to share our findings, data, code, and models with the global scientific community. We are seeking a Director of AI Infrastructure to oversee the systems that power our research. This leader will be responsible for the full lifecycle of our high-performance computing (HPC) environment which includes on-prem GPU clusters and the software orchestration layer that schedules workloads across a hybrid cloud environment. Who You Are: Systems Expert: You have a deep understanding of the Linux kernel, container runtimes, and distributed systems. You understand the performance implications of InfiniBand topologies and NCCL optimizations. Strategic Thinker: You look beyond the immediate "fire" to design systems that will scale for the next 3–5 years of AI research. Pragmatic Leader: You are comfortable making trade-offs between technical elegance and operational necessity. You prioritize reliability and researcher velocity above all else. Your Next Challenge: The essential functions include, but are not limited to the following: Cluster Management: Oversee the availability and performance of dense on-prem GPU clusters. You will partner with hardware vendors and internal teams to ensure our physical infrastructure meets the demands of frontier model training. Orchestration & Scheduling: Direct the strategy for Beaker , our internal orchestration platform. Your goal is to optimize job scheduling, ensuring high utilization of both on-prem assets and elastic cloud resources (AWS/GCP). Storage Architecture: Develop and execute a long-term roadmap for storage that balances high-throughput performance for active training with cost-effective durability for petascale research data. Resource Economics: Act as the primary steward of our GPU compute budget. You will make data-driven decisions on when to burst to the cloud versus when to invest in on-prem capacity. User Support & Velocity: Serve as the technical bridge to our research teams. You will ensure that infrastructure is an accelerator, not a bottleneck, for a diverse set of research objectives. What You’ll Need: Experience: 12+ years in infrastructure, systems engineering, or HPC, with at least 5 years in a leadership role managing multi-disciplinary engineering teams. Bachelor’s degree in related field ; relevant advanced degree may substitute for equivalent years of technical work experience GPU/HPC Stack: Direct experience managing large-scale NVIDIA GPU clusters and