LLM/NLP & Generalist AI Agents- MSc and PHD-Summer internship 2026- Research Lab

Introduction

IBM Research is at the forefront of creating intelligent systems that transform how humans interact with computers. We are currently developing the next generation of configurable

Generalist AI Agents: CUGA [https://cuga.dev, https://github.com/cuga-project/cuga-agent]. This advanced technology is designed to independently navigate and execute tasks

across complex APIs, MCP tools, web environments, and business workflows. CUGA currently ranks among the leaders in global benchmarks such as AppWorld and WebArena, leveraging advancements in Agentic AI, Large Language Models (LLMs), and Reinforcement Learning. It combines capabilities in natural language processing, model fine-tuning, and interactive decision-making. By integrating a semantic

understanding of APIs, MCP tools, and web elements with advanced action planning, CUGA aims to handle tasks that typically require significant human intervention.

Your Role And Responsibilities

We are seeking a highly motivated intern to join our research team and help advance the

field of Generalist AI agents.

As a Summer Intern, You Will

• Innovate & Develop: Design, develop, and refine cutting-edge AI agents and
  
  

• Experiment & Benchmark: Conduct rigorous experiments on leading
  
  

• Data & Prototyping: Curate datasets, fine-tune models, and demonstrate
  
  

• Research Collaboration: Collaborate with cross-functional teams of researchers
  
  

• IBM Research Lab, Israel (Haifa University Campus)
• IBM Site, Hashahar Tower, Givataim (near Tel Aviv Arlozorov train station)
  
  

• Currently enrolled M.Sc. or Ph.D. student in Computer Science, Information Systems, or a related field, with a focus on NLP, Agentic systems, and LLMs.
• Proven expertise in key domains such as LLMs/VLLMs, Transformers, Natural Language Processing (NLP), and Reinforcement Learning.
• Strong proficiency in Python development.
• Hands-on experience in implementing, training, and fine-tuning Transformers and LLMs.
  
  

• Solid understanding of AI agents and Agentic frameworks.
• Experience working with standard AI benchmarks.
• A publication track record in peer-reviewed conferences or journals is a significant- advantage.