I build AI systems that solve real problems –– be it saving people hours of work, catching issues before they become expensive mistakes, or bringing in new revenue. While my primary focus is on AI or ML engineering (depending on the project), I also emphasize full-stack development because I believe that the best AI is the kind that actually gets used –– whether or not people know it's AI.

Some keyword spam (sorry):

• My tech stack is always evolving, but my current language stack is Python, SQL, JavaScript, and TypeScript.
• My current go-to systems and frameworks for frontend are React, Next.js, Tailwind CSS, and Shadcn UI.
• I like to use FastAPI for my backend.
• I've worked with databases like PostgreSQL, Databricks, and MS SQL.
• I use Docker for containerization.
• I have experience with cloud platforms such as AWS, GCP, and Azure.
• I've worked with both GitHub and Bitbucket for version control and building CI/CD pipelines.
• As far as AI/ML APIs, I've worked with OpenAI, Anthropic, Google, and Hugging Face.
• Model development is obviously in PyTorch :)

More on traditional Machine Learning: My foundations are rooted in my academic background. I've been working towards an AI graduate certificate at Stanford maintaining a 4.0 GPA through some of the most challenging courses in the field. I've also completed an undergraduate degree in math, CS, and business data analytics (and music lol), where I graduated as the outstanding Mathematics graduate. This background enables me to approach ML challenges with deep fundamentals understanding, leading to strong models that actually make an impact on the business.

Outside my day job, my non-extracurricular time is spent either consulting local businesses for AI solutions, or as a course facilitator for Stanford's Machine Learning and AI Principles courses.