Lead Data Scientist | Kaggle Competitions Master

With over a decade of experience in data science and AI, I specialize in machine learning, NLP, computer vision, and advanced signal processing. I’ve led projects and teams, collaborating with national laboratories and cross-functional groups to solve complex challenges across various industries. While I’m passionate about staying at the forefront of AI through Kaggle Competitions, where I’m ranked in the top 1% of ~173,000 competitors, I also believe in keeping solutions practical and straightforward. I follow the "Keep It Simple" philosophy, focusing on delivering reliable, scalable results with a pragmatic approach. I'm dedicated to solving real-world problems, driving business impact through actionable insights, and sharing knowledge with the community.

• Programming Languages: Python, SQL, MATLAB, Shell Scripting
• Machine Learning Specialties: Retrieval-Augmented Generation (RAG), Generative AI, Large Language Models (LLMs), Anomaly Detection, Computer Vision, Image and Signal Processing
• Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-Learn, XGBoost, Hugging Face, LangChain, FAISS, Rapids AI, PySpark, OpenCV, Accelerate, Weights and Biases
• Cloud Platforms: AWS, GCP
• Tools & Technologies: Docker, Git, Linux, Project Management

Here are some of my GitHub repositories:

1. PyTorch and LLMs
   Implement a generic workflow and best practices for fine-tuning Large Language Models (LLMs) using PyTorch.

2. LangChain and Synthetic Data for RAG Evaluation
   Demonstrate the use of LangChain and Llama2-Chat for synthetic data generation in Information Retrieval (IR) and Retrieval Augmented Generation (RAG) evaluations.

3. Daily Object Detection Pipeline: YOLO + AWS Automate a pipeline that performs daily object detection on Columbus Circle EarthCam images using YOLOv5, deployed with AWS Lambda for seamless cloud processing and visualization.

4. StableDiffusion - Image to Text Develop and fine-tune a model capable of predicting the prompt used to create an AI generated image.

5. PII Detection and BIO Synthetic Data Generation
   Focus on personal identifiable information (PII) entity detection and performance enhancement through synthetic data generation.

6. Ecommerce Recommender System
   Build a multi-objective recommender system using candidate ranker models, optimized for large-scale e-commerce datasets, to predict user interactions such as clicks, carts, and orders.

7. LLM Serving and Inference
   Deploy large language models (LLMs) on consumer-grade CPU hardware, emphasizing high-throughput and memory-efficient inference.

For a comprehensive list of my published work, please visit my Google Scholar profile.

• AWS Certified Developer – Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer
• SQL (HackerRank)

• Email: dunlap0924@gmail.com
• GitHub: mddunlap924
• Kaggle: dunlap0924
• LinkedIn: myles-dunlap

Feel free to explore my projects and reach out for collaborations or just to chat about data science and AI!