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The Role
NLP Research Engineer Intern - CALABASAS, CA
Assignment length: 5 Months, full time from August - December of 2025 with a possibility of extension into spring of 2026.
Essential Duties:
Conduct advanced research and stay current with state-of-the-art techniques in Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs), focusing on practical applications and scalable solutions.
Design, develop, and optimize NLP models and algorithms for tasks such as semantic understanding, knowledge extraction, summarization, question answering, dialogue systems, and tool-augmented reasoning.
Collect, clean, and preprocess textual and multimodal data for training and evaluation purposes.
Contribute to the development of scalable, production-ready NLP systems, including model deployment, serving, monitoring, and lifecycle management, whether on cloud, on-premise, or edge infrastructure.
Evaluate and refine existing NLP systems by incorporating new research, benchmarking performance, and addressing failure cases.
Experiment with modern frameworks, open-source tools, and state-of-the-art foundation models using efficient adaptation techniques (e.g., low-rank adaptation, quantization-aware tuning, or other parameter-efficient fine-tuning methods).
Participate in internal research reviews, code walkthroughs, and ideation sessions.
Required Skills:
Solid grasp of NLP fundamentals, including both classical and modern techniques.
Proficient in Python and familiar with ML frameworks such as PyTorch, JAX.
Experience with NLP libraries like HuggingFace Transformers, spaCy, OpenNLP, or similar.
Familiarity with prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques for LLMs.
Understanding of contemporary architectures, including agentic orchestration and coordination frameworks, and tool-augmented systems.
Strong collaboration, communication, and documentation skills.
Experience with efficient training/fine-tuning strategies (e.g., quantization, distillation, parameter-efficient tuning)is desired.
Familiarity with agent-based systems, multi-agent collaboration, and structured reasoning techniques such as multi-hop inference and knowledge grounding is desired.
Exposure to multimodal AI models and pipelines integrating text with images, audio, or structured data is desired
Familiarity with containerization, cloud platforms (AWS, GCP) or on-premise / edge deployments is desired.
Contributions to open-source NLP/ML projects or relevant publications in top-tier venues (e.g., ACL, EMNLP, NeurIPS, ICML, ICLR, TMLR) is desired.
Knowledge of responsible AI practices, including fairness, explainability, and privacy in NLP systems is desired.
Required Education:
Pursuing or holding an M.S. or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, Applied Mathematics, Electrical Engineering, or a related technical field
Must be enrolled in an educational program to be considered as an intern
Special Requirements:
U.S. citizenship or permanent resident status required.
Compensation:
The pay range for this position is $52 - $60 per hour.
Our pay ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hires 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 range during the hiring process.
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.
What the Team is Saying
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The Company
What We Do
HRL Laboratories, LLC, Malibu, California, (hrl.com) 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. As a private company owned jointly by Boeing and GM, HRL is a source of innovations that advance the state of the art in profound and far-reaching ways.
Why Work With Us
Our success is the result of our collaborative team of researchers, many of whom are the leading experts in their fields. Through their insights in support for our customers, we are finding the unique opportunities in technology.
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HRL Laboratories Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Hybrid Policy is role specific.
Typical time on-site:
Flexible
