A bit about me:
I’m an ML Architect at 66degrees - where I’ve been building and deploying custom AI/ML solutions for the past year plus. Previously, I spent four years working as a data scientist at Accenture Research. I graduated from Northwestern in 2020 with a double-major in journalism and statistics.
I love chatting AI/ML - from cutting-edge agentic frameworks to “old-school” statistical theory. Feel free to reach out!
Some things I’m into:
🌶️ making homemade giardiniera
🏀 creating predictive models with NBA stats (download)
🎮 trying to beat Elden Ring (update: I beat it)
📰 data journalism (here’s one I love from Mona Chalabi)
⬅️ traveling to national parks!
A bit more about me, the technical stuff:
I’m skilled in developing and deploying generative AI, traditional ML, and natural language processing solutions. My project experience ranges from building retrieval-based, agentic chatbots with frameworks like Llamaindex, Langchain, and PydanticAI to training forecasting models with Tenserflow to constructing robust text processing pipelines for code generation or entity extraction.
I have worked across the breadth of the ML development cycle - scoping and system design, development and evaluation, and deployment and MLOps. In terms of tooling, I prefer Python for development. I’m also proficient in SQL and have worked extensively with relational, NoSQL, vector (Pinecone, pgvector, Milvus, etc.) and graph databases. Over the past five years, I have built and deployed my ML solutions almost entirely in Google Cloud Platform, where I’m experienced in services like Vertex AI, Compute Engine, Cloud Run / Functions, and just about every database they have to offer.
I’m trying to keep my GitHub updated with the latest stuff I’m working on, but unfortunately most of it is private!
You have reached the bottom of my site.