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
- Design and build large-scale, container-based cluster management and orchestration systems with extreme performance, scalability, and resilience.
- Architect next-generation cloud-native GPU and AI accelerator infrastructure to deliver cost-efficient and secure ML platforms.
- Collaborate across teams to deliver world-class inference solutions using vLLM, SGLang, TensorRT-LLM, and other LLM engines.
- Stay current with the latest advances in open source (Kubernetes, Ray, etc.), AI/ML and LLM infrastructure, and systems research; integrate best practices into production systems.
- Write high-quality, production-ready code that is maintainable, testable, and scalable.