Machine Learning Engineer focused on computer vision and natural language processing systems.

I'm currently working on text search and retrieval systems for trademark analysis, implementing reranking algorithms, entity clustering, and classification models. This work involves building production NLP systems that help law firms search/analyze trademark databases more effectively.

Previously, I developed high-throughput computer vision pipelines for wildlife monitoring.

Ollama-Copilot - Neovim plugin for local LLM-powered code completion. Implements language server protocol integration to provide intelligent code suggestions without cloud dependencies.

Sentence-byt5 - Research implementation exploring ByT5 architecture for sentence embeddings. Includes evaluation and technical analysis of character-level tokenization for semantic similarity tasks.

Image Captioning with Multiple Decoder Architectures - Comparative study of RNN architectures for image captioning, evaluating LSTM, GRU, and attention mechanisms on standard datasets.

YOLO Animal Pose Estimation - Fine-tuned YOLOv8 on the AP-10K dataset for animal pose detection. Explored data augmentation strategies and model optimization techniques for wildlife pose estimation.

I'm particularly interested in computer vision applications, especially object detection, re-identificaton, and embedding systems. I'm also exploring recommender systems and plan to work on projects involving collaborative filtering and content-based recommendation algorithms.

Languages

ML & Data Science

ML Engineering & Cloud

Web & Frameworks

Current Software Engineer working on ML tasks.
Auburn University graduate in Software Engineering, currently pursuing advanced coursework in artificial intelligence.

Open to collaboration on machine learning projects and opportunities in ML engineering.

Contact: LinkedIn | [email protected]