Research Scientist - AI Compute & DPU - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

What you'll do

• Research and develop infrastructure for AI workloads, including network observability, elastic storage, heterogeneous resource and power scheduling, and vector retrieval.
• Build and optimize systems that improve AI infrastructure performance, stability, resource utilization, cost, and elastic scaling.
• Explore AI-agent-based infrastructure optimization and bridge research advances with deployed systems.

What they ask for

• Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, focused on distributed and ML systems.
• First-author publications in top venues, such as OSDI, SOSP, NSDI, NeurIPS, or MLSys.
• Hands-on experience implementing or optimizing real systems beyond prototypes; strong understanding of compute, network architecture, and operating systems.
• Deep expertise in at least one area: LLM inference/AI-ML systems, AI system optimization, or software-hardware co-design; strong programming and system-design skills.

Nice to have

• High-impact research, research-to-production experience, or contributions to widely used open-source systems.
• Expertise in frontier areas such as large-scale model training/inference, heterogeneous computing, hardware-software co-design, or high-performance networking.

Tools

Kubernetes, DPDK, RDMA, GPU, DPU, FPGA/ASIC, NCCL, SPDK

AI focus

Research and develop AI infrastructure for LLMs and agents, including inference, scheduling, vector retrieval, and self-optimizing infrastructure using AI-agent workflows.