I'm a passionate and experienced Senior AI/ML Engineer based in San Francisco, CA, dedicated to building the future of autonomous systems and intelligent applications. My expertise spans large language model (LLM) orchestration, advanced computer vision techniques, and designing scalable MLOps pipelines. I thrive on transforming complex data into actionable insights and robust, production-ready AI solutions.
- Neural Nexus: A modular framework for distributed LLM training and fine-tuning across heterogeneous GPU clusters.
- Vision Core: Real-time object detection and segmentation engine optimized for edge computing devices.
- MLOps Pipeline: Automated CI/CD pipelines for machine learning models using Kubernetes and Kubeflow.
- NLP Toolkit: A Python-based natural language processing toolkit with common NLP tasks like tokenization, stemming, and sentiment analysis.
- Reinforcement Learning Gym: Implementations of various reinforcement learning algorithms (e.g., Q-learning, SARSA, DQN) using OpenAI Gym environments.
- Generative Adversarial Networks: PyTorch implementation of Generative Adversarial Networks (GANs) for image generation, including DCGAN and conditional GANs.
- Time Series Forecasting: Advanced time series forecasting models (ARIMA, Prophet, LSTM) for various applications like stock prediction and demand forecasting.
- Explainable AI Dashboard: An interactive web dashboard for visualizing and interpreting machine learning model predictions using SHAP and LIME.
Languages: Python, C++, Go
AI/ML Frameworks: TensorFlow, PyTorch, Keras, Hugging Face Transformers, NLTK, Gymnasium, Statsmodels, Streamlit, SHAP, LIME
MLOps: Kubeflow, MLflow, Docker, Kubernetes, AWS SageMaker, Azure ML
Cloud Platforms: AWS, Azure, GCP
Databases: PostgreSQL, MongoDB, Redis
- Website: sterling-ai.dev
- LinkedIn: Alexander Sterling
- Twitter: @AJSterling_AI