Research Scientist - DPU & AI Infra

What you'll do

• Develop reliable, low-latency DPU network software and optimize performance from OS kernels and drivers to user-space runtimes.
• Collaborate with hardware teams on networking and storage acceleration, and explore DPU-, GPU-, and custom-hardware-based acceleration for distributed AI training and inference.
• Contribute to architecture design, technical proposals, and long-term research directions.

What they ask for

• B.S./M.S. in Computer Science, Computer Engineering, or a related field; or a Ph.D. with strong research/publications.
• 3+ years of relevant industry experience; exception for Ph.D. candidates with a strong background.
• Proficiency in C/C++ development and debugging, and strong Linux systems development experience.
• Solid understanding of compute, network architecture, and operating systems; background in at least one of software-hardware co-design, distributed systems, high-performance networking, or AI/ML systems.

Nice to have

• Ph.D. in a related field with research training and publications; experience with software-hardware co-design.
• Experience with OVS, SR-IOV, eBPF, DPDK, hardware acceleration (FPGA/ASIC/GPU/CUDA), NCCL Collectives, AI communication and parallelization, or AI/ML infrastructure such as inference kv cache or data preprocessing systems.

Tools

C/C++, Linux, OVS, SR-IOV, eBPF, DPDK, FPGA/ASIC/GPU/CUDA, NCCL Collectives

AI focus

Accelerate AI/ML infrastructure for distributed training and inference using DPUs, GPUs, and custom hardware; optimize AI communication and parallelization, and build infrastructure such as inference kv cache and data preprocessing systems.