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

What you'll do

• Build container-based cluster management and orchestration systems focused on performance, scalability, and resilience.
• Architect cloud-native GPU and AI accelerator infrastructure for cost-efficient, secure ML platforms.
• Collaborate on LLM inference solutions and produce maintainable, production-ready code.

What they ask for

• Currently pursuing a PhD in Computer Science or a related discipline; the posting also mentions related fields with 2+ years of relevant experience, and PhD candidates with strong systems/ML publications.
• Available to work for 12 weeks during Summer 2027.
• Strong understanding of large-model inference, distributed and parallel systems, and/or high-performance networking; hands-on cloud or ML infrastructure experience.
• Knowledge of Docker and Kubernetes, and proficiency in at least one of Go, Rust, Python, or C++.

Nice to have

• Experience with large-scale cluster management, workload scheduling, GPU orchestration, scaling, or isolation.
• Experience with CUDA or LLM inference engines; familiarity with cloud ML platforms or distributed ML systems.

Tools

Docker, Kubernetes, Go, Rust, Python, C++, vLLM, SGLang

AI focus

Build GPU-optimized infrastructure and orchestration for LLM inference, integrating inference engines and supporting AI/ML workloads.