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Graph Machine Learning Research Intern Security Clearance

Job in Calabasas, Los Angeles County, California, 91302, USA
Listing for: HRL Laboratories
Apprenticeship/Internship position
Listed on 2026-03-05
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 43 - 48 USD Hourly USD 43.00 48.00 HOUR
Job Description & How to Apply Below
Position: Graph Machine Learning Research Intern with Security Clearance
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.

Essential Duties:
• 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.

Required Qualifications:

• 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).

Preferred Qualifications:

• Deep expertise in one or more of the following areas:
Graph neural networks (GNNs), graph transformers, and geometric deep learning Temporal/dynamic graph learning and event forecasting Subgraph matching and pattern discovery in large-scale graphs Distributed graph computing (GPU/TPU clusters, distributed graph engines) Heterogeneous, multi-relational, and knowledge graphs Resource-efficient, edge, or federated graph learning Graph-based reasoning, multi-hop inference, and neuro-symbolic AI Graph foundation models and multimodal graph learning Graph-augmented LLMs and agent-based reasoning on graphs Graph-based program analysis and optimization Trustworthy AI, model interpretability, and explainability

Special Requirements :
• US Citizenship and ability to obtain and maintain US Government security clearance. Compensation and Benefits:
• Pay Range : $43 - 48 an hour Our salary ranges are determined by role, level, and location (California). The range displayed on each job posting reflects the target range for new hire salaries for the position. Within the range, individual pay is…
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