Machine Learning Engineer

Details

• 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.
• 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.
• 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.
• Prolonged periods sitting at a desk and working on a computer.
• Must be able to lift up to 15 pounds at times.