Machine Learning Engineer

Lyntris is a defense technology company that connects sensing to action across the connected battlespace. The company is seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent document understanding solutions using NLP, LLMs, transformer models, and retrieval-augmented generation. The role focuses on building pipelines that convert complex technical documentation into structured, machine-actionable knowledge for search, question answering, summarization, and information extraction.

Responsibilities:

• Design, develop, and maintain NLP pipelines for technical and structured document understanding, including information extraction, summarization, semantic search, and question answering
• Build and optimize LLM-powered applications using transformer-based models, including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) architectures
• Process and analyze complex technical corpora, including engineering manuals, specifications, technical reports, drawings, tables, and figures
• Develop methods to convert unstructured and semi-structured documents into structured, machine-actionable knowledge for downstream applications
• Implement scalable machine learning solutions using Python and modern ML frameworks such as PyTorch and Hugging Face
• Evaluate model performance, improve accuracy, and optimize inference pipelines for production environments
• Collaborate with cross-functional teams, including software engineers, data scientists, and subject matter experts, to define requirements and deliver AI-enabled document intelligence solutions
• Performs other duties as assigned

Requirements:

• Bachelor's degree in Computer Science, Data Science, AI/Machine Learning, or a related technical field (or equivalent practical experience)
• 2-4 years of experience building NLP pipelines for technical or structured document understanding, including extraction, summarization, semantic search, and question answering
• Hands-on experience with large language models (LLMs) and transformer architectures (BERT and successor models), including fine-tuning, prompt engineering, pipeline orchestration, and retrieval-augmented generation (RAG)
• Experience processing complex technical documentation such as engineering manuals, specifications, technical artifacts, tables, and figures
• Strong proficiency in Python and modern machine learning frameworks, including PyTorch and Hugging Face Transformers
• Demonstrated experience converting unstructured text into structured, machine-actionable knowledge
• Currently holds an active U.S. national security clearance or be able to receive and maintain one
• Prolonged periods sitting at a desk and working on a computer
• Must be able to lift up to 15 pounds at times
• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field
• Experience deploying and maintaining production-scale NLP or LLM applications
• Familiarity with vector databases, embedding models, and semantic retrieval systems
• Experience with document parsing, OCR, layout-aware models, or multimodal document understanding
• Experience working with engineering, manufacturing, aerospace, defense, or other highly technical datasets
• Knowledge of MLOps practices, model monitoring, CI/CD pipelines, and cloud-based AI infrastructure
• Active-duty military experience