PhD Research Intern — Cloud AI Systems & HPC

ByteDance; San Jose (CA); On-site; USD 68,000 - 97,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

Paid holidays

Housing allowance

Job summary

ByteDance invites PhD students to join the DPU team for a 12-week Summer 2027 internship in San Jose, CA. You will design and build large-scale, container-based cluster management and GPU/AI accelerator infrastructure, collaborating across teams to deliver inference solutions.

We value hands-on contributors with strong background in distributed systems, cloud ML infrastructure, and experience with Docker, Kubernetes, and modern ML frameworks; excellent communication across global teams is a plus.

Qualifications

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
• Able to commit to working for 12 weeks during Summer 2027
• Strong understanding of large model inference, distributed and parallel systems, and/or high-performance networking systems.
• Hands‑on experience building cloud or ML infrastructure in areas such as resource management, scheduling, request routing, monitoring, or orchestration.
• Solid knowledge of container and orchestration technologies (Docker, Kubernetes).
• Proficiency in at least one major programming language (Go, Rust, Python, or C++).

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.

Skills

Go

Rust

Python

C++

Distributed systems

Large model inference

Education

PhD candidate (CS/CE/EE)

Tools

Docker

Kubernetes

TensorRT

Ray

SGLang

vLLM

Job description

ByteDance invites PhD students to join the DPU team for a 12-week Summer 2027 internship in San Jose, CA. You will design and build large-scale, container-based cluster management and GPU/AI accelerator infrastructure, collaborating across teams to deliver inference solutions.

We value hands-on contributors with strong background in distributed systems, cloud ML infrastructure, and experience with Docker, Kubernetes, and modern ML frameworks; excellent communication across global teams is a plus.