Research Scientist Internship 2027 (Yorktown Heights, Cambridge)

Job Description

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 for IBM Software, building technologies that IBM customers rely on today and in the future.

As an intern, you will advance agent architectures and domain-specific models for business processes, IT and industrial automation, and software engineering across distributed and non-distributed environments. You will also develop responsible AI systems and enterprise-grade benchmarks that help enterprises personalize services, automate operations, optimize workflows, predict demand, and deliver outcomes.

As an AI Research Scientist Intern, you will take part in the full research lifecycle. Your work will include identifying core challenges, designing prototype solutions, and validating them through rigorous experimentation. Research areas include foundation models and multimodal AI, business process intelligence and automation, IT and industrial automation, AI for software engineering, reliable and scalable agentic systems, AI security and trustworthiness, enterprise knowledge graphs, continual agent learning and adaptation, and knowledge-guided workflow orchestration.

You will work in small, mentored teams and be responsible for taking projects from ideation to completion. A key goal 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.

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 in modern AI and systems, through hands-on work and theoretical foundations in foundation and multimodal models, agentic systems, AI for software engineering, knowledge graphs, continual learning, process intelligence, or distributed systems.
• Strong programming and prototyping skills in Python for rapid prototyping, experimental setup, and large-scale machine learning systems.
• Quantitative analysis, experiment design, and the ability to break down complex research problems.
• A track record of innovation, shown through peer-reviewed publications or strong preprints, and the ability to explain complex technical concepts in writing and presentations.
• A team-oriented approach with a commitment to rigorous, reproducible, and well-documented research.
• A strong publication record in top-tier conferences such as NeurIPS, ICML, ICLR, CVPR, or AAAI.
• Advanced expertise in ML frameworks (PyTorch) and full-cycle development of algorithms and systems.
• Hands-on experience with generative AI (LLMs) and multimodal models, from training to testing.
• Ability to present complex research and build high-impact technical demonstrations.