Applied AI Research Intern - R&D Internship - 2027 Yorktown Heights & Cambridge

Introduction Join the pioneering Software Innovation Lab team at IBM Software and contribute to shaping the future foundations of artificial intelligence and data. Our group of scientists and engineers are dedicated to conducting end-to-end research that delivers real-world AI impact through a rigorous, responsible, and open innovation framework. We are the R&D team that is the innovation engine of IBM Software. We are shaping the technologies that IBM customers rely on – today and in the future. As an intern, you will explore cutting-edge research areas, with a focus on AI models and approaches for 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, semantic stream processing for stored and streaming data. You will explore efficiency, accuracy and scalability challenges, test new theories, design experiments to validate novel computational models, all within a collaborative environment that bridges fundamental science and transformative engineering. Your Role And Responsibilities As an AI Research Scientist Intern, you will engage in the full research lifecycle to pioneer new advancements in artificial intelligence and data management. Your role will involve identifying core challenges, designing novel prototype solutions, and validating them through rigorous experimentation. You will conduct foundational research in critical areas such as developing and evaluating stream-native AI, including novel real-time AI-based services to agents; multi-agent synthetic skill synthesis, refinement and reuse with coding agents; transforming event streams into hybrid world models; and query and context optimization for novel, integrated streamed and stored data management. Collaborating in small, mentored teams, you will be responsible for shepherding projects from ideation to completion. A key objective is to disseminate significant results through publications in leading conferences and patent applications, contributing to both the academic community and IBM's open innovation initiatives. Program Dates Internship start dates vary based on your academic calendar. Semester System: May 24, 2027 – August 13, 2027 Quarter System: June 14, 2027 – September 3, 2027 Location Flexibility By applying to this requisition, you acknowledge and agree to be considered for any of the listed locations associated with this position and are willing to work at the location where you are ultimately assigned. Preferred Education Doctorate Degree Required Technical And Professional Expertise Research Experience with Modern ML: Hands-on experience with and a deep theoretical understanding of Large Language Models (LLMs) and transformer-based architectures. 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, 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 challenges and systems. Experience with stream processing is a plus. Communication: Demonstrated ability to present complex research and build high-impact technical demonstrations. #J-18808-Ljbffr