SWE: Toward Autonomous Data Management with AI Intern 2026

Description du poste:

Introduction

IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing, always choosing the big, urgent and mind-bending work that endures and shapes generations. Our passion for discovery, and excitement for defining the future of tech, is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make.

IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive.

Your role and responsibilities

We are looking for a talented and motivated intern to join our team and help build the next generation of autonomous data management systems. In this role, you will work with foundation models (FMs) and AI agents to make data systems smarter, easier to use, and more efficient.

Topics include but are not limited to:
* Using large language models (LLMs) for code generation, such as writing SQL/NoSQL queries or Python code for analytics.
* Exploring how knowledge graphs and multi-modal data can be combined with LLMs to improve data discovery and question answering.
* Improving the performance and efficiency of AI model inference.
* Building generative AI tools for DataOps (like DevOps, but for data engineering and analytics).

This internship is a great fit for students who are:
* Pursuing an undergraduate degree or masters in computer science or a related field
* Excited about AI, agentic AI, data systems, and software engineering
* Comfortable with programming (Python, SQL, or similar languages)
* Curious and eager to learn how AI can be applied to real-world data problems

Required education
High School Diploma/GED

Preferred education
Bachelor's Degree

Required technical and professional expertise

* Pursuing education in computer science and related fields
* Familiarity and working expertise with large language models

Preferred technical and professional experience

* Familiarity with knowledge graphs, SQL, RAG, and agentic frameworks
* Familiarity with reinforcement learning and AI planning
* Familiarity with prompt optimization techniques