Research Engineer/Scientist, R&D Internship

About the Role

Join the pioneering Software Innovation Lab team at IBM Software and contribute to shaping the future foundations of artificial intelligence. Our group of scientists and engineers conducts end-to-end research within a rigorous, responsible, and open innovation framework.

As an intern, you will explore cutting-edge research areas including:

• Data management and processing
• Building systems where AI plans, uses external APIs, and executes multi-step tasks independently
• Developing enterprise agents with rigorous evaluation gates and compliance guardrails
• Identifying new algorithms for training and fine-tuning LLMs

Your Role And Responsibilities

As an AI Research Scientist Intern, you will engage in the full research lifecycle to pioneer new advancements in streaming and batch data processing & management and artificial intelligence. Your role will involve:

• Identifying core challenges
• Designing novel prototype solutions
• Validating them through rigorous experimentation
• Conducting foundational research in critical areas such as agentic systems and databases, novel training algorithms, efficient fine-tuning, agentic architectures and their application to the data domain.
• Collaborating in small, mentored teams to shepherd projects from ideation to completion.
• Disseminating significant results through publications in leading conferences and patent applications.

Program Dates:

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

Candidates must be available to participate for the full duration of the internship corresponding to their academic schedule.

Location Flexibility:

Consideration for any listed locations associated with this position.

Qualifications

Preferred Education:

• Doctorate Degree

Requirements & Tech Stack

Required Technical and Professional Expertise:

• 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 technologies such as Kafka, Flink, PostgreSQL, Lakehouse, and SQL.
• Strong Programming & Prototyping Skills: Proficiency in Python for rapid prototyping, experimental setup, and implementing large-scale machine learning systems.
• Rigorous Analytical & Problem-Solving Abilities: Demonstrated strength in quantitative analysis, designing experiments, and deconstructing complex research problems.
• Proven Research & Communication Skills: A track record of innovation (evidenced by peer-reviewed publications or strong preprints) and the ability to clearly articulate complex technical concepts in both writing and presentations.
• Collaborative Research Mindset: A team-oriented approach with a commitment to rigorous, reproducible, and well-documented research practices.

Preferred Technical and Professional Experience:

• Research Excellence: Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, VLDB, SIGMOD etc).
• 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.