Cloud Acceleration Research Intern - DPU & AI Infra

About the Team The ByteDance DPU (Data Processing Unit) team builds foundational cloud and AI computing infrastructure for ByteDance and Volcano Engine. Our mission is to advance the architecture, development, and research of next-generation software-hardware co-design technologies across compute, networking, and storage for cloud and AI computing. Our technology stack spans - Cloud virtualization, hypervisors, and operating systems - High-performance networking, including DPDK and RDMA - High-speed interconnects, virtual switching, and network offload - Distributed storage and I/O acceleration - Orchestration and scheduling for AI/ML workloads We work at the intersection of systems research, distributed infrastructure, and hardware acceleration. Our technologies operate at cloud scale and help shape the next generation of cloud and AI computing platforms. We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date). Responsibilities - Conduct research and development in DPU-based cloud acceleration and large-scale AI infrastructure. - Explore software-hardware co-design opportunities for AI/ML infrastructure, leveraging DPUs, GPUs, and custom hardware to optimize distributed training and inference. - Develop new techniques for accelerating distributed AI training and inference, including communication, data movement, resource management, and memory or cache systems. - Perform end-to-end performance analysis and optimization across hardware, device drivers, operating-system kernels, communication libraries, and user-space runtimes. - Build prototypes and evaluate proposed designs using representative cloud and AI workloads at scale. - Collaborate with hardware architects, systems engineers, and AI infrastructure teams to transition research ideas into production. - Contribute to technical proposals, architecture designs, publications, patents, and longer-term research directions Minimum Qualifications - Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field. - Able to commit to a full-time, 12-week internship during Summer 2027. - Proficiency in C/C++ or Rust, including systems-level development and debugging. - Strong Linux systems development experience - Solid understanding of operating systems, computer architecture, networking, or distributed systems. - Background in at least one of: software-hardware co-design, computer architecture, distributed storage systems, high-performance networking, or AI/ML systems. Preferred Qualifications - Record of research demonstrated through publications, technical reports, open-source contributions, or substantial research projects. - Experience designing, implementing, and evaluating production-quality or research prototype systems. - Familiarity with one or more of the following: - DPDK, RDMA, eBPF, or high-performance communication libraries - Hypervisors, kernel bypass, device virtualization, or hardware offload - LLM serving, disaggregated inference, or KV-cache management - Distributed data loading, preprocessing, or storage systems - Performance modeling, profiling, or benchmarking - Strong analytical, creative problem-solving, and communication skills. - Ability to work effectively across research, software, and hardware teams.