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Description
Introduction
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk
Your Role And Responsibilities
The job responsibilities include working with a team of world-class researchers to help define and develop novel large language models, AI agents, and foundation models projects. The primary mission for the team is to lead the definition of the autonomous AI agents, agent architectures and middleware components capable of planning, reasoning, and interacting with complex environments. Investigate memory, tool use, and long-term behavior in agentic systems. Key responsibilities will include proposing new concepts in AI agents, large language models and machine learning. Further responsibilities include performing research and development of machine learning, NLP, large language models, agents and agentic middleware and evaluating their merits relative to state-of-the-art solutions, and demonstrating external eminence by publishing the outcomes of the research in top-tier conferences (e.g., NeurIPS, ICML, ACL, ICLR) and journals; contribute to open-source projects and engage with the broader AI research community through talks, workshops, and collaborations.
Preferred Education
Doctorate Degree
Required Technical And Professional Expertise
Strong software engineering background, and proficiency in Python programming as well as experience with state-of-the-art software collaboration practices is essential. Deep expertise in machine learning systems and architecture, with a track record of developing AI models and agents.
Passionate about advancing research in AI systems, particularly in agents, agentic middleware and large language models.
Preferred Technical And Professional Experience
Experience with the use and adaptation of Deep Learning frameworks including TensorFlow and PyTorch Strong background in deep-learning applications including large language models.
