Research Scientist Graduate (DPU & AI Infra) - 2027 Start (PhD)

What you'll do

• Develop and evaluate techniques and prototypes for accelerating distributed AI training and inference at scale.
• Analyze and optimize performance across hardware, drivers, operating-system kernels, communication libraries, and runtimes.
• Contribute to architecture design, technical proposals, and long-term research directions.

What they ask for

• Ph.D. in a related field, with research training and publications.
• Proficiency in C/C++ or Rust, including systems-level development and debugging.
• Familiarity with Linux systems development.
• Solid understanding of operating systems, computer architecture, networking, or distributed systems; background in at least one listed area such as software-hardware co-design or AI/ML systems.

Nice to have

• Experience with software-hardware co-design, network virtualization, or DPDK and high-performance user-space networking.
• Hardware acceleration, NCCL Collectives, AI communication and parallelization, or AI/ML infrastructure experience.

Tools

C/C++, Rust, Linux, OVS, SR-IOV, eBPF, DPDK, NCCL Collectives

AI focus

Research and optimize AI/ML infrastructure for distributed training and inference, including communication, data movement, resource management, memory/cache systems, and hardware acceleration.