Daniel Brown

About Daniel Brown

Experienced Senior Machine Learning Engineer with a strong background in NLP, cybersecurity, predictive maintenance, and supply chain optimization, specializing in deploying AI-driven solutions for edge computing, defense, and enterprise systems. Proven expertise in designing scalable ML pipelines, real-time anomaly detection models, and AI-powered automation using Python, PyTorch, TensorFlow, and cloud platforms (AWS/GCP/Azure). Adept at building high-performance microservices, optimizing ML inference for edge devices, and integrating AI models with mission-critical systems to enhance decision-making and operational efficiency. Passionate about applying AI/ML to solve complex business challenges, ensuring secure, scalable, and efficient software solutions for modern enterprises.

Experience

1. Senior Machine Learning Engineer Generative Ai

   Mercury Systems

   Aug 2021 — Present · Andover, MA, US

   NLP for Cybersecurity & Threat Detectiono Developed on-device NLP models using Python, PyTorch, and TensorFlow to analyze network logs and communication patterns, detecting anomalies with 92% accuracy in real-time.o Applied sentiment analysis and toxicity detection with LLMs (GPT, Llama, Mistral, Claude, Gemini) to identify hostile intent, reducing false positives in threat classification by 30%.· Named Entity Recognition (NER) & Retrieval-Augmented Generation (RAG) for Intelligence Processingo Engineered low-latency transformer-based NER models optimized with ONNX and TensorRT, achieving 40% faster inference on edge devices.o Integrated RAG architectures with LLMs (GPT, Llama, Mistral, Claude, Gemini) to enhance intelligence retrieval, boosting query relevance by 35% in real-time decision-making systems.· Conversational AI & Chatbot Developmento Designed and deployed LLM-powered chatbots using Hugging Face Transformers and FastAPI, improving automated intelligence briefings by 40%.o Developed edge-deployable conversational AI assistants for military analysts, reducing response time in mission-critical scenarios by 35%.· Knowledge Graphs & Semantic Search for Defense Intelligenceo Built NLP-driven knowledge graphs using Neo4j and Elasticsearch, improving structured intelligence processing across documents.o Implemented semantic search with RAG and LLMs (GPT, Llama, Mistral, Claude, Gemini), reducing time-to-insight for military analysts by 40%.

Education

• Tennessee Technological University

  Bachelors

  2011 — 2014