- Conduct advanced research in LLMs, Generative AI, and agentic AI systems, staying current with rapidly evolving techniques such as tool-augmented reasoning, planning agents, and multi-agent collaboration.
- Design and prototype LLM-based agents capable of reasoning, planning, tool invocation, memory management, and autonomous task execution.
- Develop and optimize retrieval-augmented and tool-augmented generation pipelines (RAG, Graph-RAG, hybrid search, vector & symbolic retrieval).
- Build and evaluate end-to-end agent workflows, including orchestration, tool APIs, state tracking, and long-horizon planning.
- Implement robust evaluation pipelines for LLMs and agents (offline evals, LLM-as-judge, human-in-the-loop evaluation, red-teaming, and safety validation).
- Experiment with open-source and frontier foundation models (e.g., Llama, Mistral, Claude, Gemini, GPT-class models) and efficient adaptation techniques.
- Contribute to scalable production systems, including model serving, orchestration frameworks, observability, guardrails, and lifecycle management.
- Participate in internal research reviews, technical deep dives, and code walkthroughs.
- Currently pursuing M.S. or Ph.
- Strong foundation in machine learning and NLP, including transformers, attention mechanisms, and modern generative modeling.
- Proficiency in Python and modern ML frameworks such as PyTorch, JAX, or TensorFlow.
- Hands-on experience with LLM tooling and frameworks, such as: HuggingFace, LangChain, LlamaIndex, Haystack, or similar orchestration frameworks
- Familiarity with agentic AI patterns, including Tool use / function calling, Planning & reasoning (ReAct, Tree/Graph of Thoughts, etc.), Memory architectures (short-term, long-term, vector DBs)
- Experience with RAG pipelines, embeddings, and vector databases.
- Understanding of prompting strategies, fine-tuning, and alignment techniques (SFT, RLHF/DPO, PEFT/LoRA).
- Strong software engineering practices, including version control, testing, and documentation.
- Ability to communicate technical concepts clearly and collaborate in a research-engineering environment.
- Experience building autonomous or semi-autonomous agent systems in real applications.
- Familiarity with multi-agent systems, coordination, and distributed reasoning.
- Knowledge of evaluation and benchmarking frameworks for LLMs and agents
- Experience with model optimization techniques: Quantization, distillation, speculative decoding, KV-cache optimization
- Exposure to knowledge graphs, symbolic reasoning, or hybrid neuro-symbolic AI systems.
- Contributions to open-source AI/ML projects or publications (ACL, NeurIPS, ICML, ICLR, etc.).
- US Citizenship and ability to obtain and maintain US Government security clearance.
- 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 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.
- For more information about our company benefit offerings please visit:
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LLM & Agentic AI Research Intern - Calabasas - HRL Laboratories LLC
Description
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:
Required Qualifications:
Preferred Qualifications:
Familiarity with deployment stacks:
Docker/Kubernetes, model serving, GPU/accelerator pipelines
Special Requirements:
Compensation and Benefits:
Pay Range:
$43 - $48 an hour
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
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 CommissionFor our privacy policy please visit:
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.-
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