Research Intern (Frontier AI Systems) - 2027 Start (PhD)

What you'll do

• Research and build prototypes for next-generation AI systems and infrastructure.
• Analyze system bottlenecks and trade-offs; develop realistic benchmarks for efficiency, scalability, robustness, and cost.
• Collaborate with researchers and engineers to communicate findings and shape future infrastructure directions.

What they ask for

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or a related technical field.
• Strong background in at least one area such as ML systems, distributed systems, large-scale training, inference, reinforcement learning systems, storage, networking, or infrastructure engineering.
• Strong systems intuition and analytical ability to reason about model behavior, runtime performance, and system-level trade-offs.
• Ability to work independently in ambiguous technical spaces; strong written and verbal communication and collaboration skills.

Nice to have

• Experience with large-scale training, post-training, reinforcement learning, inference, or serving systems.
• Familiarity with retrieval, AI memory, agentic workloads, or large-scale infrastructure concepts; research publications or systems prototypes are also valued.

Tools

RDMA, NCCL, KV cache

AI focus

Research and develop AI systems and infrastructure, including training, reinforcement learning, inference, retrieval, AI memory, agent workflows, and AI methods for infrastructure optimization.