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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Agentic AI & Graph Machine Learning Research Engineer - **Company:** Hrl Laboratories Llc - **Location:** Calabasas, CA, United States - **Experience:** Experienced - **Salary:** $128,000.0 - $159,950.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Cloud Engineering, Query Languages, Decision Support Systems, Distributed Systems, Graph Database, Interoperability, Python (Programming Language), Machine Learning, Natural Language Processing, Neo4j, Software Engineering, Data Streaming, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Deep Learning, Generative AI, Information Technology, Optimization Algorithms, Machine Learning Operations, Virtual Agents, Software Version Control - **Published:** July 31, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6f48b70ca03120a4 ## About the Role * Minimum: M.S. in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Network Science, or a related technical field plus 3+ years of relevant industry or research experience in AI/ML * Strong background in machine learning, deep learning, natural language processing, generative AI, and multimodal foundation models * Experience adapting and optimizing foundation models through prompt engineering, supervised fine tuning, parameter efficient fine tuning, preference optimization, model alignment, and inference optimization techniques * Experience developing LLM powered and agentic AI systems using modern agent frameworks (e.g., LangGraph, AutoGen, or equivalent) * Familiarity with AI interoperability standards and distributed agent architectures, including Model Context Protocol (MCP), Agent2Agent (A2A), or comparable frameworks for tool integration and multi agent communication * Hands on experience with graph mining, graph matching, geometric deep learning, and applied GML workflows * Experience with knowledge graphs, ontologies, graph schemas (e.g., LPG, RDF), graph databases (e.g., Neo4j), and graph query languages (e.g., Cypher) * Proficiency in Python, PyTorch, and modern software engineering practices (version control, testing, collaborative development) * Experience with large scale data processing and distributed systems (e.g., Ray, Spark), and optionally real time streaming or online learning pipelines * Experience deploying scalable AI systems using modern LLMOps/AgentOps, distributed inference, GPU acceleration, model serving frameworks (e.g., vLLM, SGLang), observability, and cloud native infrastructure, * Ph.D. in a relevant technical discipline with research experience in agentic AI, foundation models, graph machine learning, geometric deep learning, autonomous systems, or related areas * Prior research publications in top tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, KDD, WWW, AAAI) are highly desirable Special Requirements: * U.S. Citizenship with the ability to obtain and maintain a U.S. Government Security Clearance ## Description * Lead and conduct research in agentic AI, intelligent decision support, autonomous workflows, and LLM-powered agent architectures integrating memory, planning, tool use, and retrieval * Design, develop, and evaluate multi-agent systems for distributed decision-making, coordination, communication, and long-horizon task execution across mission-critical domains and applications * Build knowledge-enhanced AI systems that integrate structured knowledge sources, including knowledge graphs, GraphRAG pipelines, ontologies, and multimodal retrieval systems to improve reasoning and context awareness * Develop and apply graph machine learning (GML) and graph representation learning techniques (e.g., GNNs, geometric deep learning) to support pattern discovery, anomaly detection, and predictive analytics * Develop trustworthy AI systems, including Explainable AI (XAI), Verification & Validation (V&V), robustness testing, uncertainty quantification, and safety assessments for agentic and graph-based AI systems * Collaborate with multidisciplinary teams, publish high-quality research, support proposal development, and engage with internal and external stakeholders ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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