Greater Seattle Area
I'm a machine learning engineer, data scientist, and software developer focused on building systems that work at scale. I've worked across diverse domains including content safety, healthcare, forensics, and retail—collaborating with teams at Meta, Parabon NanoLabs, and Profitect on deep technical challenges. As an engineer, I like to understand the full scope of a problem—prototyping ideas, working through architecture decisions, writing production code. I'm drawn to work that sits at the intersection of research and practical application, whether that's deploying deep learning models, building medical data pipelines, or shipping containerized web apps. I enjoy digging into hard problems, asking questions until things click, and finding solutions that hold up in production. From my academic background teaching math and statistics at Harvard and Wellesley, I've learned that technical work is only valuable if you can explain it clearly. I try to bring that same mindset to cross-functional collaboration—breaking down complex systems, focusing on what matters, and keeping stakeholders on the same page. Good engineering isn't just about the code; it's about solving the right problem and working well with the people around you. What drives me: challenging problems, thoughtful teams, and work that makes a tangible difference.