PhD Research Intern: Agentic AI & LLM Systems

IBM; Cambridge (MA); On-site; USD 44,000 - 69,000; Full time

Job summary

IBM Research Cambridge invites a PhD student to participate in a 2027 summer internship within the AI Native Systems group to advance efficient, reliable agentic AI for IBM Z. The role centers on large language models, AI agents, adaptive memory management, and enterprise infrastructure in Finn/Paver frameworks.

You will collaborate with IBM researchers and academia, implement prototypes in Python, and contribute to publications and potential IP disclosures with real-world impact.

Qualifications

• PhD candidate in Computer Science, Electrical Engineering, or a related field.
• Experience with machine learning, LLMs, AI agents, NLP.
• Strong Python programming and ML framework experience (PyTorch, TensorFlow).

Responsibilities

• Research, design, and prototype adaptive information-control mechanisms for agentic AI systems.
• Define and model minimal sufficient agent state including observations, memory, and task progress.
• Develop and evaluate information acquisition, retrieval, summarization, and memory management techniques.
• Implement experimental solutions in Python and integrate into Finn/Paver or similar agent framework.
• Design experiments on z/OS management tasks measuring reliability, memory, latency, and efficiency.
• Analyze tradeoffs between performance, information efficiency, cost, and on-platform execution.
• Collaborate with researchers to review results and translate findings into practical architectures.
• Document outcomes through reports, presentations, demos, or IP disclosures.

Skills

Python

PyTorch

TensorFlow

NLP

AI research

Large language models

Education

Doctorate Degree

Tools

Hugging Face

Job description

IBM Research Cambridge invites a PhD student to participate in a 2027 summer internship within the AI Native Systems group to advance efficient, reliable agentic AI for IBM Z. The role centers on large language models, AI agents, adaptive memory management, and enterprise infrastructure in Finn/Paver frameworks.

You will collaborate with IBM researchers and academia, implement prototypes in Python, and contribute to publications and potential IP disclosures with real-world impact.