Weston S.
Senior AI/ML Architect | Data Scientist | Agentic Engineer | GCP, AWS
๐ฅ ๐ฆ๐ฒ๐ป๐ถ๐ผ๐ฟ ๐๐/๐ ๐ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐ | ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐๐ถ๐๐ | ๐๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ | ๐๐ผ๐ผ๐ด๐น๐ฒ ๐๐น๐ผ๐๐ฑ ๐ฃ๐ฟ๐ฒ๐บ๐ถ๐ฒ๐ฟ ๐ฃ๐ฎ๐ฟ๐๐ป๐ฒ๐ฟ | ๐ญ๐ฌ+ ๐๐ฒ๐ฎ๐ฟ๐ ๐ผ๐ณ ๐ฒ๐ ๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ฅ A highly accomplished and results-driven AI/ML Architect with over 10 years of experience, specializing in architecting and deploying advanced AI/ML solutions for enterprise clients across diverse industries including airline, automotive, marketing analytics, political outreach, and fact-checking for publishers. My background spans the entire AI/ML lifecycle, from strategic solution design to hands-on implementation and operationalization of scalable, real-world systems. I'm currently leading the team at AI Arch Solutions to excel at translating complex business challenges into innovative, AI-driven solutions that deliver measurable ROI. ๐ช ๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐ ๐ช ๐ผ๐๐๐๐ฉ๐๐ ๐ผ๐ฐ & ๐จ๐ช๐๐ค๐๐ค๐๐ค๐๐จ ๐๐๐จ๐๐๐๐จ โ ๐๐ด๐ฒ๐ป๐ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ๐: ReAct (Reasoning and Acting), RAG (Retrieval-Augmented Generation), Multi-Agent Systems (MAS), Hierarchical Agent Architectures (e.g., Manager-Worker) โ ๐๐ผ๐ฟ๐ฒ ๐๐ด๐ฒ๐ป๐ ๐๐ฏ๐ถ๐น๐ถ๐๐ถ๐ฒ๐: Tool Use & Function Calling, Complex Task Decomposition, Dynamic Planning & Reasoning, Self-Correction & Reflection Loops (e.g., Reflexion) โ ๐ ๐ฒ๐บ๐ผ๐ฟ๐ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐: Designing and implementing agent memory systems, including short-term (context window), long-term (vector databases), and structured memory approaches โ ๐ฃ๐ฟ๐ผ๐บ๐ฝ๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด & ๐ฆ๐๐ฎ๐๐ฒ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐: Advanced prompt chaining, state tracking across multi-turn interactions, and managing conversational context for complex tasks ๐ซ๐๐๐ ๐๐๐๐๐ฃ๐๐ & ๐ฟ๐๐ฉ๐ ๐ฌ๐ฃ๐๐๐๐๐๐ง๐๐ฃ๐ โ ๐ ๐ผ๐ฑ๐ฒ๐น ๐ฃ๐ฟ๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐๐ถ๐ผ๐ป: Data cleaning, data imputation, feature engineering, feature space reduction (PCA) โ ๐ ๐ผ๐ฑ๐ฒ๐น ๐๐ ๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ: LLMs, Neural Networks, NLP (BERT, ELMO, GPT Variants), K-Means / Hierarchical Clustering, Logistic Regression, Random Forest (XGBoost), K-Nearest Neighbor, Naรฏve Bayes, GridSearch, Causal Inference, Bayesian Marketing Mix Modeling โ ๐๐ฎ๐๐ฎ ๐ฉ๐ถ๐๐๐ฎ๐น๐ถ๐๐ฎ๐๐ถ๐ผ๐ป๐: Tableau, Seaborn, Matplotlib, Plotly, Dash โ ๐๐ผ๐ฑ๐ถ๐ป๐ด: Python (NumPy, pandas, scikit-learn, TensorFlow, Keras, NLTK, LangChain, Streamlit), SQL, Java, R โ ๐๐ฎ๐๐ฎ ๐ง๐ผ๐ผ๐น๐: Google Cloud Platform (BigQuery, Vertex AI), AWS (SageMaker, Lambda, S3), Databricks, Airflow (DAGs), Pinecone, PostgreSQL โ ๐๐ ๐ฝ๐ฒ๐ฟ๐ถ๐บ๐ฒ๐ป๐๐ฎ๐๐ถ๐ผ๐ป: Regression Discontinuity Design, Interrupted Time Series, A / B Testing