AI Systems & Cloud Infrastructure Intern

ByteDance; San Jose (CA); On-site; USD 50,000 - 83,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

Housing allowance

Paid holidays

Paid sick time

Job summary

ByteDance is seeking PhD students for a Summer 2027 internship to contribute to our DPU team, building scalable cloud-native GPU and AI accelerator infrastructure, and advancing LLM inference platforms. You will work with vLLM, SGLang, TensorRT-LLM, and related technologies across cloud and AI systems.

You will collaborate with global teams, gain hands-on experience, and participate in professional development events designed for researchers and engineers pursuing cutting-edge cloud and AI

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 open source and AI/ML infrastructure advances; integrate best practices into production systems.
• Write high-quality, production-ready code that is maintainable, testable, and scalable.

Skills

Large model inference

Distributed systems

High-performance networking

Cloud infrastructure

Container orchestration

Programming: Go/Python/C++

Education

PhD in CS/CE/EE or related

Tools

Docker

Kubernetes

Job description

ByteDance is seeking PhD students for a Summer 2027 internship to contribute to our DPU team, building scalable cloud-native GPU and AI accelerator infrastructure, and advancing LLM inference platforms. You will work with vLLM, SGLang, TensorRT-LLM, and related technologies across cloud and AI systems.

You will collaborate with global teams, gain hands-on experience, and participate in professional development events designed for researchers and engineers pursuing cutting-edge cloud and AI