ByteDance
Research Intern (AI Compute) - 2027 Start (PhD)
San Jose, California · Internship · Posted Oct 28, 2026
- Education
- Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
About the job
Research and build scalable cloud-native infrastructure for GPU and AI workloads, including cluster orchestration and LLM inference systems.
What you'll do
- Design and build high-performance, resilient container-based cluster management and orchestration systems.
- Architect cloud-native GPU and AI accelerator infrastructure for cost-efficient, secure ML platforms.
- Collaborate on LLM inference solutions and deliver production-ready code.
What they ask for
- Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
- Able to commit to 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.
- Knowledge of Docker and Kubernetes, and proficiency in at least one of Go, Rust, Python, or C++.
Nice to have
- Experience with cluster management, workload scheduling, GPU orchestration, scaling, or isolation in production.
- Experience with CUDA or inference engines, or familiarity with public cloud and ML platforms.
Tools
Kubernetes, Ray, vLLM, SGLang, TensorRT-LLM, Docker, Go, Rust
AI focus
Build GPU and AI accelerator infrastructure and develop LLM inference solutions.
Model-written summary · the original posting is authoritative