- New Jersey - États-Unis d'Amérique
Multi-agent Software Architectures Researcher - Internship
Multi-agent Software Architectures Researcher - Internship
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 thrive 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 Foundational Technology (FT) is the central R&D department of Siemens and thus has a key role to shape the future of our products. FT acts as a strategic partner to support the executive units of Siemens. In consequence 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 semantic technologies, to create the next generation of flexible, and intelligent 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 preferred to be on-site in Princeton, NJ, for a hands-on and collaborative experience, however remote candidates will be considered. The position is a full-time role for at least 3 months with the possibility of extension.
Key Responsibilities
- Conduct cutting-edge research into the principles and mechanisms for AI-driven self-organization and dynamic composition within complex software architectures.
- Develop and evaluate novel algorithms and frameworks that enable software components to dynamically organize and orchestrate themselves based on stated user needs and objectives.
- Design and implement proof-of-concept prototypes to demonstrate the feasibility and effectiveness of dynamic system composition and intelligent component interaction.
- Investigate methods and strategies to ensure repeatability and determinism in the outcomes of AI-driven, self-organizing software systems.
- Explore and apply advanced AI techniques for interpreting intents, understanding component capabilities, and facilitating intelligent software composition and adaptation.
- 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.
Basic Qualifications
- Currently enrolled in a PhD program in Computer Science, Artificial Intelligence, or a closely related technical field.
- 1+ year(s) Foundational knowledge and research experience in Artificial Intelligence, Machine Learning and GenAI.
- 1+ year(s) Understanding of microservice architectures, cloud-native principles, and distributed computing concepts.
- Demonstrated ability to conduct independent research, critically analyze complex problems, and propose innovative solutions.
- Experience with fine tuning of LLM (e.g., LoRA) and training/testing ML models.
- 1+ year(s) Advanced knowledge of transformer-based models, attention mechanisms, and the latest LLM architectures (e.g., GPT, BERT, encoder-decoder).
- Proficient in Python and ML frameworks (e.g., Pytorch, HF transformers or similar).
- Experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate, Chroma or other).
- Background knowledge in representation and semantic technologies (e.g.,RDF, SPARQL, OWL).
- Proficient in English both written and verbal
- The position does require the person to be in the United States of America and hold a valid work permit for the US.
Preferred Skills
- Prior research experience in AI, distributed systems, or autonomous systems, demonstrated through academic publications, thesis work, or significant project contributions.
- Hands-on expertise with Large Language Models (LLMs), including fine-tuning, prompt engineering, or integration into system design.
- Familiarity with semantic technologies, knowledge graphs, ontology engineering, or symbolic AI.
- Aptitude for quickly learning and adopting new technologies and frameworks.
- Proficiency with containerization technologies (e.g., Docker, Kubernetes) and major cloud platforms (e.g., Azure, AWS).
- Knowledge of agent-based systems, multi-agent systems, or autonomous systems.
- Background in AI Agentic frameworks and platforms (e.g., LangGraph, Semantic Kernel, NeMo).
- The ability to articulate complex technical concepts clearly.
- Skill in working with graph databases (e.g., Neo4j, AWS Neptune) and knowledge graph toolsets (e.g., Altair Graph Studio).
- Competence with RAG frameworks.
- Capability in deploying and serving LLMs (e.g., vLLM).
- Track record of contributing to research publications, open-source projects, or significant academic projects.
- Excellent problem-solving skills and attention to detail.
- Capacity to work independently and manage time effectively.
About Siemens:
We are a global technology company focused on industry, infrastructure, transport, and healthcare. From more resource-efficient factories, resilient supply chains, and smarter buildings and grids, to sustainable transportation as well as advanced healthcare, we create technology with purpose adding real value for customers.
Our Commitment to Diversity, Equity, and Inclusion:
We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society. Come bring your authentic self and create a better tomorrow with us. Learn more about our commitment to DEI here.
Protecting the environment, conserving our natural resources, fostering the health and performance of our people as well as safeguarding their working conditions are core to our social and business commitment at Siemens. They are an integral part of our Business Conduct Guidelines and our corporate strategy.
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Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $26.00-$47.00 per hour. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications and premium geographic location.
Déclaration d’égalité des chances en matière d’emploi
Siemens est un employeur garantissant l’égalité des chances, qui promeut l’inclusion sur le lieu de travail. Tous les candidats qualifiés seront examinés pour un emploi sans distinction de race, couleur, croyance, religion, origine nationale, statut de citoyenneté, ascendance, sexe, âge, handicap physique ou mental sans lien avec les capacités, statut marital, responsabilités familiales, grossesse, informations génétiques, orientation sexuelle, expression ou identité de genre, transidentité, stéréotypes liés au sexe, statut de protection, statut d’ancien combattant ou militaire protégé, ou encore en cas de libération défavorable du service militaire, ainsi que toute autre catégorie protégée par la législation fédérale, étatique ou locale.
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Les candidats et employés sont protégés contre toute discrimination fondée sur la race, la couleur, la religion, le sexe, l’origine nationale ou toute autre caractéristique protégée par la loi fédérale ou toute autre législation applicable.
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