Applied AI Research Intern (Multiple Cities)

Applied AI Research Intern at IBM Software

Join the Software Innovation Lab team at IBM Software and help shape the future of artificial intelligence and data. Our scientists and engineers conduct end-to-end research that delivers real-world AI impact through a rigorous, responsible, and open innovation framework. We are the R&D team driving innovation across IBM Software, building technologies that IBM customers rely on today and in the future.

As an intern, you will explore cutting-edge research areas, focusing on AI models and approaches for a real-time data and context backbone for agents and stream-native AI. Topics include hybrid world models, real-time context optimization for agents and models, and semantic stream processing for stored and streaming data. You will examine efficiency, accuracy, and scalability challenges, test new theories, and design experiments to validate novel computational models.

As an AI Research Scientist Intern, you will take part in the full research lifecycle. You will identify core challenges, design novel prototype solutions, and validate them through rigorous experimentation. Key research areas include:

• Developing and evaluating stream-native AI, including real-time AI-based services for agents
• Multi-agent synthetic skill synthesis, refinement, and reuse with coding agents
• Transforming event streams into hybrid world models
• Query and context optimization for integrated streamed and stored data management

You will work in small, mentored teams and be responsible for taking projects from ideation to completion. A key objective is to share significant results through publications in leading conferences and patent applications, contributing to the academic community and IBM's open innovation initiatives.

Program Dates

Start dates vary based on your academic calendar:

• Semester System: May 24, 2027 to August 13, 2027
• Quarter System: June 14, 2027 to September 3, 2027

Candidates must be available for the full duration of the internship that matches their academic schedule.

Location Flexibility: By applying, you agree to be considered for any listed location for this position and to work at the location where you are ultimately assigned.

Requirements

• Research Experience with Modern ML: Hands-on experience and a deep theoretical understanding of Large Language Models (LLMs) and transformer-based architectures.
• Programming and Prototyping: Proficiency in Python for rapid prototyping, experimental setup, and implementing large-scale machine learning systems.
• Analytical and Problem-Solving Abilities: Strength in quantitative analysis, experiment design, and breaking down complex research problems.
• Research and Communication: A track record of innovation (peer-reviewed publications or strong preprints) and the ability to clearly explain complex technical concepts in writing and presentations.
• Collaborative Research Mindset: A team-oriented approach with a commitment to rigorous, reproducible, and well-documented research.
• Research Excellence: Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, VLDB, SIGMOD, AAAI).
• Technical Proficiency: Advanced expertise in ML frameworks (PyTorch) and full-cycle development of algorithms and systems.
• Specialized Skills: Hands-on experience with generative AI (LLMs), from training to testing, applied to data management. Experience with stream processing is a plus.
• Communication: Ability to present complex research and build high-impact technical demonstrations.