Our team’s mission is to architect, co-design, and productionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost. Our work spans today’s frontier AI workloads and directly shapes the next generation of accelerators, system architectures, and large-scale AI platforms. We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.

Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.

Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.

Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.

Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.

Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.

Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.

Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.

Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.