AI Native Systems Research Scientist Intern 2027

Join a team conducting cutting-edge research in AI Native Distributed Systems. In this role, you will explore and advance one or more of many aspects of AI-native distributed computing we are currently working on, including: design, development, and optimization of software platforms for building, deploying, and managing large language models (LLMs) and agents; principles, methodologies, and frameworks for AI-native software development, evolution, and optimization; high-performance distributed inference for LLMs; frameworks, tools, and infrastructure that support the end-to-end AI lifecycle;

networking for AI infrastructure, developing/prototyping networking solutions and techniques for future AI systems, including networking for distributed inference and RDMA over Ethernet networking, as well as evaluation of the solutions from performance, scalability, and resiliency perspectives; networking innovations that enable high-performance communication for AI workloads and emerging distributed inference patterns.

The ideal candidate has a strong foundation in AI, large language models, and agentic workloads, combined with expertise in systems, networking, or software engineering. As an intern, you will contribute across the full industrial research lifecycle: formulating novel ideas, designing and building prototype systems, evaluating performance at scale, demonstrating real-world impact, and publishing results in leading scientific venues.