Brandon Wheat

- Architected and developed an AI-powered interview preparation platform from conception to deployment, integrating React, Supabase, and Google's Gemini API - Implemented secure authentication and payment processing systems using Row Level Security (RLS) and Stripe integration - Designed and built a scalable business-facing feature allowing companies to create custom interview templates with shareable links - Developed real-time voice communication capabilities using WebRTC and AI multimodal APIs, ensuring seamless user experience - Successfully managed all aspects of development including frontend, backend, security, and systems architecture

- Engineered a full-stack smart cocktail system combining IoT, AI, and web technologies: - Developed custom wake word detection model using TensorFlow, achieving robust performance through innovative training data generation - Implemented dual-mode voice interaction system utilizing Deepgram, Anthropic's Claude, and OpenAI APIs - Built responsive web interface using SvelteKit with FastAPI backend, enabling remote control and monitoring - Designed complete hardware solution including CAD modeling, sensor integration, and IoT control systems - Implemented containerized deployment using Docker and OTA updates via Mender for reliable system maintenance - Created real-time communication architecture using Redis pub/sub for seamless component interaction

• Authored automation scripts to streamline and optimize operational processes, increasing efficiency, and reducing manual intervention
• Coordinated with a diverse team to formulate and implement architecture of a comprehensive high-frequency trading simulator in Python, with a focus on building a robust inheritance structure that allows for easy integration and modification of components for future enhancements
• Played a key role in designing and implementing the frontend display for simulation results to ensure clear, user-friendly visualization of complex trading data
• Implemented a WebSocket-based communication layer, facilitating real-time, bi-directional data exchange between the server and frontend, enhancing the responsiveness and interactivity of the Simulator
• Implemented a real-time machine learning model for sentiment analysis using NLP techniques, integrating insights into trading strategies to predict stock movements
• Crafted a model to identify unusual trading volumes at earnings releases, aiding in swift trading decisions

• Maintained and updated website, ensuring search engine optimization best practices; Collaborated with cross-functional teams for content management

• Developed security code to identify and block suspicious or malicious user activity; Significantly reduced manual effort by automating billing processes

• Vulnerability analysis and penetration testing