Research Intern (Inference Infrastructure) - 2027 Start (PhD)

ByteDance is a technology company building cloud and AI computing infrastructure through its DPU team. The Research Intern will design and build scalable cluster management, cloud-native GPU, AI accelerator, and inference infrastructure while collaborating on LLM solutions and developing production-ready systems code.

What you'll do:

• 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

What they're looking for:

• 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++)
• Experience contributing to or operating large-scale cluster management systems (e.g., Kubernetes, Ray)
• Experience with workload scheduling, GPU orchestration, scaling, and isolation in production environments
• Hands-on experience with GPU programming (CUDA) or inference engines (vLLM, SGLang, TensorRT-LLM)
• Familiarity with public cloud providers (AWS, Azure, GCP) and their ML platforms (SageMaker, Azure ML, Vertex AI)
• Strong knowledge of ML systems (Ray, DeepSpeed, PyTorch) and distributed training/inference platforms
• Excellent communication skills and ability to collaborate across global, cross-functional teams

Benefits:

• Interns have day one access to health insurance, life insurance, wellbeing benefits and more.
• Interns also receive 10 paid holidays per year.
• Interns also receive paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).
• Interns who are not working 100% remote may also be eligible for housing allowance.