Architecture & Engineering of Systems Researcher Internship

Architecture & Engineering of Intelligent Systems Researcher Internship

Princeton, New Jersey, United States of America

Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first.

Our global, diverse team would be happy to support you and challenge you to grow in new ways.

Siemens Research & Predevelopment (RPD) is the central R&D department of Siemens and thus has a key role to shape the future of our products. RPD acts as a strategic partner to support the executive units of Siemens. Consequently, the main research focus is on future technologies for industry, infrastructure, mobility, and healthcare. In this context, we are looking for an Intern that supports our Software Systems and Processes team in Princeton, NJ by researching and developing scalable intelligent systems using LLMs and semantic technologies.

Are you passionate about pushing the boundaries of AI and software engineering? We’re looking for an innovative PhD intern to join our team and contribute to a groundbreaking research project focused on advanced agentic AI software architectures and their dynamic capabilities.

Modern software systems are evolving rapidly, requiring components that can intelligently adapt, self‑organize themselves to fulfill complex objectives. The challenge lies in enabling these intelligent software elements to dynamically orchestrate their behaviors and interactions based on stated intents, moving beyond today's more rigid, predefined structures. This role offers a unique opportunity to research and develop novel approaches that empower software architectures to dynamically adapt, ensuring repeatable and robust outcomes within specified constraints.

You’ll be at the forefront of leveraging advanced AI, including Large Language Models (LLMs), knowledge graphs, and other semantic technologies, to create the next generation of flexible and intelligent industrial software systems.

The internship provides a unique experience to contribute to innovative industrial applications while mentored by experienced professionals in an international setting.

This role is on‑site in Princeton, NJ, for a hands‑on and collaborative experience; however remote candidates may be considered
. The position is a full‑time role for at least 3 months with the possibility of extension.

• Conduct cutting‑edge research into the principles and mechanisms for AI‑driven self‑evolution and dynamic composition within complex industrial software systems.
• Develop and evaluate novel algorithms and frameworks that enable software components to dynamically evolve, adapt, and orchestrate themselves based on stated user needs and objectives.
• Design innovative AI‑powered approaches to solve industrial use‑cases based on consultation with domain experts and research advisors.
• Design and implement proof‑of‑concept prototypes and corresponding experiments to demonstrate feasibility and effectiveness in industrial contexts.
• Investigate methods and strategies to ensure repeatability and determinism in the outcomes of AI‑driven self‑evolving software systems.
• Collaborate closely with the research team to define project milestones, analyze results, and contribute to the overall research agenda.
• Document research findings thoroughly, contribute to scientific publications, and present results at internal and external forums.

• Currently enrolled in a PhD program in Computer Science, Artificial Intelligence, Software Engineering, or a closely related technical field.
• 3+ years of foundational knowledge and research experience in Artificial Intelligence, Machine Learning, GenAI, or Software Engineering.
• 3+ years of hands‑on experience with Python and ML frameworks (e.g., PyTorch, HF Transformers or similar).
• 1+ year of hands‑on experience with semantic technologies, knowledge graphs, ontology engineering, or symbolic AI.
• 1+ year of…