Graph Machine Learning Research Intern
Calabasas, California, United States of America
Internship
2 days ago
$86,000 - $96,000 USD
Key skills
PythonJavaC++CGoAIArtificial IntelligenceMachine LearningMLDeep LearningNLPComputer VisionLarge Language ModelsPyTorchAnalyticsSparkNeo4jDecision Making
About this role
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, TigerGraph), 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, WWW, 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 hourOur 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 determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process. • Benefits: HRL offers a generous and very competitive total compensation and benefits package. Our Regular/Full Time benefits include medical, dental, vision, life insurance, 401K match, gym facilities, PTO, Sick time, upward mobility, and an exciting and challenging work environment. • For more information about our company benefit offerings please visit: https://www.hrl.com/careers/benefits
Non-Discrimination and Equal Employment Opportunities (U.S.)Don’t meet every single requirement? Studies have shown that some people are less likely to apply to jobs unless they meet every single desired qualification. At HRL, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
We are proud to be an EEO/AA employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing.
If you would like more information about Equal Employment Opportunity as an applicant under the law, please go to Employees & Job Applicants | U.S. Equal Employment Opportunity Commission
For our privacy policy please visit: www.hrl.com/privacy
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, TigerGraph), 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, WWW, 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 hourOur 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 determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process. • Benefits: HRL offers a generous and very competitive total compensation and benefits package. Our Regular/Full Time benefits include medical, dental, vision, life insurance, 401K match, gym facilities, PTO, Sick time, upward mobility, and an exciting and challenging work environment. • For more information about our company benefit offerings please visit: https://www.hrl.com/careers/benefits
Non-Discrimination and Equal Employment Opportunities (U.S.)Don’t meet every single requirement? Studies have shown that some people are less likely to apply to jobs unless they meet every single desired qualification. At HRL, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
We are proud to be an EEO/AA employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing.
If you would like more information about Equal Employment Opportunity as an applicant under the law, please go to Employees & Job Applicants | U.S. Equal Employment Opportunity Commission
For our privacy policy please visit: www.hrl.com/privacy