Graph Machine Learning Research Intern

Join Us for an Unforgettable Summer Internship Experience!

Looking to grow your skills, build your network, and have a little fun along the way? Our Summer Internship Program offers the perfect mix of hands‑on experience and community‑building activities designed to support both your personal and professional development.

Over the course of the summer, you’ll dive into meaningful work that will expand your knowledge and challenge you to think creatively. But it’s not all work—we believe in balance.

• Connect with fellow interns and early‑career professionals through engaging networking event
• Unwind with movie nights, beach days, and celebrate National Intern Day
• Explore our cutting‑edge science during two half days of guided laboratory tours, where you’ll visit 8 of our top research facilities and see innovation in action
• Whether you’re looking to kick‑start your career or simply learn more about the exciting work we do, this is more than just an internship—it’s your first step into a vibrant, supportive, and forward‑thinking community.

HRL Laboratories pioneers the next frontiers of physical and information science. Delivering transformative technologies in automotive, aerospace and defense, HRL advances the critical missions of its customers to help them remove limitations and create competitive advantage. HRL then transitions the work back to customers – ready for real‑world application. For more than 70 years, HRL’s rich portfolio of scientific discoveries and engineering innovations continues to build on each other — often in unexpected, profound and far‑reaching ways.

As a private company owned jointly by Boeing and GM, HRL prioritizes purpose over profit, significantly advancing the state of the art.

HRL Laboratories develops robust intelligent systems that deliver adaptable, autonomous performance improvement solutions for complex missions. Our teams advance human‑machine synergy, operationalized machine learning models and complex systems analytics and agents to create scalable, secure technologies. We design novel algorithms and mission‑ready solutions that strengthen decision making for autonomous and human‑guided systems across national security and commercial applications.

• Lead and contribute to cutting‑edge research in graph computing and graph machine learning (GML).
• Design, develop, and evaluate algorithms for graph representation learning, reasoning, and analytics on dynamic, heterogeneous, and large‑scale graphs.
• Apply GML to high‑impact domains such as cybersecurity, finance, social science, material science, and intelligent systems.
• Integrate GML with foundation models (e.g., large language models/LLMs, multimodal models) for tasks like knowledge graph reasoning, graph‑augmented retrieval, and trustworthy decision support.
• Translate research insights into deployable prototypes and production‑level software.
• Author technical publications, invention disclosures, and research presentations for internal and external stakeholders, and support proposal and business development activities.

• Currently pursuing an M.S. or Ph.D. in Computer Science, Network Science, Artificial Intelligence, Applied Mathematics, or a closely related discipline.
• Hands‑on experience with graph mining, graph matching, geometric deep learning, and applied GML problems.
• Proficiency in Python (preferred) or another major programing language (e.g., C++, Java) and deep learning libraries and frameworks (e.g., PyTorch Geometric).
• Experience with knowledge graphs, ontologies, graph schemas (e.g., RDF, LPG), graph databases (e.g., Neo4J, Tiger Graph), and query languages (e.g., Cypher, SPARQL).
• Experience with large‑scale data processing and distributed systems (e.g., Ray, Spark), and optionally with real‑time streaming pipelines or online learning pipelines.
• Experience with bridging GML with NLP, computer vision, multi‑modal AI, and agent‑based systems.
• Track record of peer‑reviewed publications in premier AI/ML venues (e.g., NeurIPS, ICLR, KDD,(Use the "Apply for this Job" box below). AAAI, ICML, SIGMOD).

• Graph neural networks (GNNs), graph transformers, and geometric…