Research Internship in San Jose

Join the Software Innovation Lab team at IBM Software and help shape the foundations of artificial intelligence. 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, shaping technologies that IBM customers rely on today and in the future.

As an intern, you will explore cutting-edge areas including data management and processing, systems where AI plans, uses external APIs, and executes multi-step tasks independently, enterprise agents with rigorous evaluation gates and compliance guardrails, new training algorithms, and fine-tuning of LLMs. You will work through the full research lifecycle to advance streaming and batch data processing and artificial intelligence. Your work will involve identifying core challenges, designing prototype solutions, and validating them through rigorous experimentation.

You will conduct foundational research in agentic systems and databases, novel training algorithms, efficient fine-tuning, agentic architectures, and their application to the data domain. Working in small, mentored teams, you will take projects from ideation to completion. A key goal is to share significant results through publications in leading conferences and patent applications, contributing to both the academic community and IBM software products and 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 to this requisition, you agree to be considered for any of the listed locations associated with this position and to work at the location where you are ultimately assigned.

Requirements

• Research Experience with Modern ML: Hands-on experience with agentic AI and a deep theoretical understanding of Large Language Models (LLMs), task specific small language models, and Transformer-based architectures. Understanding of Kafka, Flink, PostgreSQL, Lakehouse, and SQL.
• Strong Programming and Prototyping Skills: Proficiency in Python for rapid prototyping, experimental setup, and implementing large-scale machine learning systems.
• Analytical and Problem-Solving Abilities: Demonstrated strength in quantitative analysis, experiment design, and breaking down complex research problems.
• Research and Communication Skills: A track record of innovation (evidenced by 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 practices.
• Research Excellence: Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, VLDB, SIGMOD).
• 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) and agentic systems, from training to testing.
• Communication: Demonstrated ability to present complex research and build high-impact technical demonstrations.