LLM/NLP- Generalist AI Agent- MSC/PHD Student- Research Lab

Introduction

IBM Research leads the way in creating intelligent systems that transform how humans interact with computers. We are currently developing the next generation of Generalist AI Agents, advanced technology designed to independently navigate and execute tasks across complex APIs, MCP tools, web environments, and business workflows.

Our Generalist AI agents are currently leading globally in benchmarks like Appworld and WebArina, utilizing advances in Agentic AI, Large Language Models, and Reinforcement Learning. They combine skills in natural language processing, model fine-tuning, and interactive decision-making. By integrating semantic understanding of APIs, MCP tools, and web elements with advanced action planning, these agents aim to handle tasks that typically require significant human intervention.

Your Role And Responsibilities

We are seeking a motivated intern to join our research team and contribute to advancing Generalist AI agents. As an intern, you will:

• Design, develop, and refine cutting-edge AI agents and Agentic frameworks, incorporating advanced technologies such as LLMs, multimodal models, and reinforcement learning systems.
• Conduct rigorous experiments on leading benchmarks, including WebArena and BrowserGym, to assess and enhance the capabilities of AI agents.
• Curate datasets, fine-tune models, and showcase performance through early-stage prototypes for web-based automation solutions.
• Collaborate with cross-functional teams of researchers and engineers to publish findings in top venues and drive innovation within IBM’s groundbreaking solutions.
  
  

• 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 AI.
• Proven expertise in key areas such as LLMs/VLLMs, Transformers, Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
• Hands-on experience in implementing, training, and fine-tuning Transformers and LLMs.
  
  

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