Cloud Acceleration Research Intern (DPU & AI Infra) - 2027 Start (PhD) PhD Intern - 2027 Start San Jose

ByteDance; San Jose (CA); Hybrid; USD 60,000 - 80,000; Full time

Job summary

ByteDance is seeking a Cloud Acceleration Research Intern (DPU & AI Infra) for a 2027 start. The internship is based in San Jose within the Technology team.

This PhD-oriented role focuses on research and development of DPU-based cloud acceleration and AI infrastructure, exploring co-design opportunities across hardware and software. You will contribute to optimizing distributed AI training and inference, conduct performance analyses, and build prototypes to evaluate new acceleration techniques.

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 using 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, OS kernels, communication libraries, and user-space runtimes.
• Build prototypes and evaluate proposed solutions.

Job description

Cloud Acceleration Research Intern (DPU & AI Infra) - 2027 Start (PhD)

Location:

San Jose

Team:

Technology

Employment Type:

Intern

Job Code:

A26730

Responsibilities

About the TeamThe 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 workloadsWe 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.

• - 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