AI Platform- MSc and PHD-Summer internship 2026- Research Lab

Introduction

At IBM, a job is more than work. We build, collaborate, and design the future. We learn and envision how our clients can leverage cutting edge technologies. Are you ready to grow and lead in this new era of technology and tackle some of the world’s most challenging problems? If so, let’s talk.

Your Role And Responsibilities

The IBM Research Lab in Israel is seeking exceptional students to join our dynamic team to work on optimizing AI inference platforms, exploring how to streamline and optimize AI inference platforms, such as vLLM and llm-d, for running AI and Agentic workloads. Our team focuses on developing core technologies to enable running the next generation of AI applications and workloads. This includes:

• Explore and optimize the AI inference platform for heterogenous AI and Agentic workloads.
• Optimize performance and accuracy trade-offs for high scalable inference systems.
• Explore and leverage how heterogenous models (e.g., small, large, generic, pre-trained) can optimize AI workloads.
• Develop and evaluate new platform algorithms leveraging the behavior of AI and Agentic frameworks.
  
  

• Design and implement algorithms for optimizing inference, e.g., KV-cache mechanisms, LLM context optimizations, etc.
• Develop code (e.g., in Python and GO) for enterprise AI inference
• Performing benchmarking and evaluation and gain expertise in AI platforms
• Gain hands-on experience with enterprise AI software stack, tools and platforms
• Leverage AI capabilities to accelerate the exploration and development of algorithms
• Work in a global company gaining team and collaboration practices
  
  

• Your academic transcript.
• Open-source work/contributions if available.
  
  

• MSC/PHD Student in Computer Science / Software Engineering / Information Systems 
• Research topic in the areas of AI, distributed systems or related area
• Hands-on coding experience, strong programming and problem-solving skills
• Good command of English
• Team player with high motivation and self-learning ability
  
  

• PhD students
• Experience with large language models inference or architecture.