Brandon Snelgrove

Led development of SentraCore, a GenAI cybersecurity platform that cut investigation time by 35%. Architected NeuroStack AI, a multimodal assistant integrating an LLM/RAG chatbot, a CNN vision model, and a Reinforcement Learning engine, increasing automation efficiency by 40%.

Spearheaded development of a real-time fraud detection system, improving precision by 15% and reducing false positives by 22%. Built end-to-end MLOps pipelines using TensorFlow Extended (TFX) for continuous retraining and automated deployment, enabling adaptation to evolving fraud tactics.

Deployed a BERT-based sentiment classifier on AWS SageMaker that processed millions of reviews in real-time, reducing manual moderation by over 60%. Pioneered generative AI initiatives by fine-tuning GPT-2 for chatbot prototypes and content generation, utilizing Kubeflow to orchestrate model training jobs.

Developed machine learning models for retail and finance, including a customer churn prediction model and an NLP-based document classifier. Processed large-scale datasets using Spark and SQL, collaborating with data engineers to deploy models into production pipelines.

Assisted in building the company's first data analytics and ML pipelines. Performed extensive data cleaning, feature engineering, and exploratory data analysis (EDA) on raw client data.

Completed a Bachelor of Science in Computer Science, gaining foundational knowledge in programming, algorithms, and data structures. This program prepared me for entry-level roles in software development and data analysis.

Earned a Master of Science in Computer Science, focusing on advanced topics in machine learning and artificial intelligence. This graduate program deepened my expertise in complex algorithms and system design.